Split (1)

train · 2.06k rows

source stringlengths 26 381	text stringlengths 53 1.64M
https://www.databricks.com/glossary/jupyter-notebook	What is a Jupyter Notebook?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWJupyter NotebookAll>Jupyter NotebookTry Databricks for freeGet StartedWhat is a Jupyter Notebook?A Jupyter Notebook is an open source web application that allows data scientists to create and share documents that include live code, equations, and other multimedia resources.What are Jupyter Notebooks used for?Jupyter notebooks are used for all sorts of data science tasks such as exploratory data analysis (EDA), data cleaning and transformation, data visualization, statistical modeling, machine learning, and deep learning.What are the benefits of using Jupyter Notebooks?Jupyter notebooks are especially useful for "showing the work" that your data team has done through a combination of code, markdown, links, and images. They are easy to use and can be run cell by cell to better understand what the code does.Jupyter notebooks can also be converted to a number of standard output formats (HTML, Powerpoint, LaTeX, PDF, ReStructuredText, Markdown, Python) through the web interface. This flexibility makes it easy for data scientists to share their work with others.How do Jupyter Notebooks work?A Jupyter notebook has two components: a front-end web page and a back-end kernel. The front-end web page allows data scientists to enter programming code or text in rectangular "cells." The browser then passes the code to the back-end kernel which runs the code and returns the results.What are the downsides of using Jupyter Notebooks?Difficult to maintain and keep in sync when collaboratively working on code.Difficult to operationalize your code when using Jupyter notebooks as they don't feature any built-in integration or tools for operationalizing your machine learning models.Difficult to scale — Jupyter notebooks are designed for single-node data science. If your data is too big to fit in your computer's memory, using Jupyter notebooks becomes significantly more difficult.Are Jupyter Notebooks available on Databricks?Looking for a powerful data science collaboration tool? Look no further than Databricks! Our notebooks allow you to work together with colleagues across engineering, data science, and machine learning teams in multiple languages, with built-in data visualizations, and operationalization with jobs. Sign up for a free trial.Does Databricks offer support for Jupyter Notebooks?Yes. Databricks clusters can be configured to use the IPython kernel in order to take advantage of the Jupyter ecosystem's open source tooling (display and output tools, for example). Databricks also offers support for importing and exporting .ipynb files, so you can easily pick up right where you left off in your Jupyter notebook, on Databricks — and vice versa. Finally, Databricks has long supported the core open source Jupyter libraries within the Databricks Machine Learning Runtime.How to use the IPython kernel on DatabricksIt's easy. View the documentation, then sign up for a free trial of Databricks. Additional ResourcesCollaborative Notebooks - DatabricksJupyterLab-Databricks Integration Bridges Local and Remote WorkflowsNotebook Gallery: Example notebooks for data science, data engineering, ML and moreBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/dataaisummit/speaker/justin-breese	Justin Breese - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJustin BreeseSr. Product Manager at DatabricksBack to speakersJustin is a Product Manager at Databricks and works on areas like query processing and SQL. He has a ton of interests: soccer, hiking, brewing beer, roasting coffee, and older cars. Justin lives in Topanga, CA with his wife and a baby boy (due in July).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/product/pricing/delta-live	Delta Live Tables Pricing \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWWorkflows & Streaming: Delta Live Tables PricingOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorDelta Live TablesEasily ingest and transform batch and streaming data on the Databricks Lakehouse PlatformSelect planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudLoading...Compare featuresDLT Core DLT Core PhotonDLT Pro DLT Pro PhotonDLT Advanced DLT Advanced PhotonSQL APIPython APIStreaming TablesContinuous PipelinesAuto-Loader IntegrationObservability Metrics with Event LogTable LineageAccess Controls (ACL)Enhanced AutoscalingChange Data Capture (CDC) (link)Slowly Changing Dimension (SCD) Type 2 (Preview)Data Quality Expectation RulesData Quality Expectation PoliciesData Quality ObservabilityPhoton Engine Performance (Massively parallel processing)Optional (DBU emission rate 2.9x vs. non-Photon. See the Pricing calculator.)Observability Data Retention5 days 30 days 30 days Governance and ManageabilitySee Platform Capabilities and Add-Ons for detailsEnterprise SecuritySee Platform Capabilities and Add-Ons for detailsPay as you go with a 14-day free trial or contact us for committed-use discounts or custom requirements. Calculate priceStart free trialContact usFAQ Can I pick a different DLT Product Edition for each pipeline in my workspace?Yes. You can specify a different edition for each DLT pipeline in the pipeline settings.How do I select a DLT Product Edition for my pipeline?You will have the option to choose a DLT product edition when a pipeline is created. Simply click “Create Cluster” from the Delta Live Tables page, and you will see an option to choose the DLT product edition on the subsequent window.Am I able to change the DLT Product Edition after I’ve created the pipeline?Yes. You may change the DLT Edition of a pipeline at any time through the DLT settings UI.What happens if I attempt to set DLT quality expectations and my pipeline is not using the Advanced Edition?When you attempt to run a pipeline that includes features which are not included in the DLT Product Edition selected for that pipeline, you will receive an error message that will include a reason for the error. You may then modify the product edition for the pipeline to choose an edition that includes the desired feature, and attempt to re-run the pipeline.Are there any other charges associated with DLT?Yes, a DLT cluster will automatically run a periodic system-generated job to maintain the Delta Live Table that will consume DBUs at the Jobs Compute Rate.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/dataaisummit/speaker/matthew-powers	Matthew Powers - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMatthew PowersDeveloper Advocate at DatabricksBack to speakersMatthew is a Developer Advocate for Databricks on the Delta Lake team. He's a longtime Spark blogger (mungingdata.com) and Spark open-source contributor. His project include quinn, chispa, spark-daria, spark-fast-tests, and the spark-style-guide. He's passionate about Spark, Delta Lake, traveling, and learning languages.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/harrison-chase	Harrison Chase - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHarrison ChaseCEO at LangChainBack to speakersHarrison Chase is the co-founder and CEO of LangChain, a company formed around the open-source Python/Typescript packages that aim to make it easy to develop Language Model applications. Prior to starting LangChain, he led the ML team at Robust Intelligence (an MLOps company focused on testing and validation of machine learning models), led the entity linking team at Kensho (a fintech startup), and studied stats and CS at Harvard.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/company/partners/consulting-and-si	Databricks Consulting Partners - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Consulting PartnersConnect with Databricks Partners globally to help you build, deploy or migrate to the Databricks Lakehouse PlatformDatabricks Consulting Partners are experts uniquely positioned to help you implement and scale data engineering, collaborative data science, full-lifecycle machine learning and business analytics initiatives. They bring technology, industry and use case expertise to help you make the most of the Databricks Lakehouse Platform. Services include designing a data transformation strategy unique to your business, data modernization and migration, data management and governance, and much more.Loading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/product/delta-sharing	Delta Sharing \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDelta SharingAn open standard for secure sharing of data assetsGet StartedWatch DemoDatabricks Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform.Key benefitsOpen cross-platform sharingAvoid vendor lock-in, and easily share existing data in Delta Lake and Apache Parquet formats to any data platform.Share live data with no replicationShare live data across data platforms, clouds or regions without replicating or copying it to another system.Centralized governanceCentrally manage, govern, audit and track usage of the shared data on one platform.Marketplace for data productsBuild and package data products, including data sets, ML models and notebooks once and distribute anywhere through a central marketplace.Privacy-safe data cleanroomsEasily collaborate with your customers and partners on any cloud via a secure hosted environment while safeguarding data privacy.How it worksNative integration with the Databricks platformNative integration with the Unity Catalog allows you to centrally manage and audit shared data across organizations. This lets you confidently share data assets with suppliers and partners for better coordination of your business while meeting security and compliance needs.Easily manage sharesCreate and manage providers, recipients, and shares with a simple-to-use UI, SQL commands or REST APIs with full CLI and Terraform supportDiscover and access data products through an open marketplaceEasily discover, evaluate and gain access to data products including data sets, machine learning models, dashboards and notebooks from anywhere, without the need to be on the Databricks platform.Privacy-safe data cleanroomsCollaborate with your customers and partners on any cloud in a privacy-safe environment. Securely share data from your data lakes without data replication. Meet collaborators on their preferred cloud and provide them the flexibility to run complex computations and workloads in any language — SQL, R, Scala, Java and Python. Guide collaborators through common use cases using predefined templates, notebooks and dashboards, accelerating time to insights.Use casesInternal line of business sharingBuild Data Mesh with Delta Sharing to securely share data with business units and subsidiaries across clouds or regions without copying or replicating the data.B2B SharingData monetizationCustomers“Delta Sharing helped us streamline our data delivery process for large data sets. This enables our clients to bring their own compute environment to read fresh curated data with little-to-no integration work, and enables us to continue expanding our catalog of unique, high-quality data products.”— William Dague, Head of Alternative Data“As a data company, giving our customers access to our data sets is critical. The Databricks Lakehouse Platform with Delta Sharing really streamlines that process, allowing us to securely reach a much broader user base regardless of cloud or platform.”— Felix Cheung, VP of Engineering“Leveraging the powerful capabilities of Delta Sharing from Databricks enables Pumpjack Dataworks to have a faster onboarding experience, removing the need for exporting, importing and remodeling of data, which brings immediate value to our clients. Faster results yield greater commercial opportunity for our clients and their partners.”— Corey Zwart, Head of Engineering“With Delta Sharing, our clients can access curated data sets nearly instantly and integrate them with analytics tools of their choice. The dialogue with our clients shifts from a low-value, technical back-and-forth on ingestion to a high-value analytical discussion where we drive successful client experiences. As our client relationships evolve, we can seamlessly deliver new data sets and refresh existing ones through Delta Sharing to keep clients appraised of key trends in their industries.”— Anup Segu, Data Engineering Tech LeadAn open ecosystemAccess the latest published version directly from the provider in easy-to-use SQL, Python or BI tools.ResourcesKeynote and Webinar[Keynote] Data Governance and sharing on the lakehouse at Data + AI Summit 2022[On-demand Webinar] Accelerate Business Value With Delta SharingBlogsAnnouncing General Availability of Delta SharingIntroducing Delta Sharing: An Open Protocol for Secure Data SharingTop Three Data Sharing Use Cases With Delta SharingSolution Sheet & eBook[eBook] Explore the new Delta Sharing SolutionDelta Sharing: An open standard for secure data sharingRise of the Data Lakehouse by Bill Inmon, father of the data warehouseReady to get started with Databricks?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesTerms of UseWebsite Terms of UseThese terms of use (“Terms”) govern your access to and use of all Databricks-branded publicly available websites, including sites located on databricks.com (other than .cloud.databricks.com and help.databricks.com), as well as spark-summit.org, and spark-packages.org and any other pages that link to these Terms (collectively, the “Sites”). 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https://www.databricks.com/dataaisummit/speaker/gregory-little/#	Gregory Little - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGregory LittleDCDAO for Enterprise Platforms and Business Optimization at DoD CFO Transformation OfficeBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/jp/p/whitepaper/mit-cio-vision-2025?itm_data=home-promocard2-mit-cio-vision-2025	2025 年に向けた CIO のビジョン：AI と BI の連携 \| Databricksレポート2025 年に向けたCIO のビジョンAI と BI の連携AI の導入に関するグローバルな調査結果実践的な AI 活用をめざすうえで最大の課題となるのが「データの問題」です。トップ企業はこの課題をいかにして解決しているのでしょうか。MIT テクノロジーレビュー・インサイトによる、18 か国、14 業種のエグゼクティブ 600 名を対象とした最新の調査レポートで詳しく解説しています。（日本語版をダウンロードしていただけます。）AI の導入に関する CIO（最高情報責任者）の思索とは？データ戦略への投資において重視すべき要件とは？プロクター・アンド・ギャンブル（P&G）、ジョンソン・エンド・ジョンソン（J&J）、東京海上、S&P グローバル、マークス＆スペンサーをはじめとする大手企業の経営幹部クラスのエグゼクティブに対するインタビューから、深い知見が得られました。今回の調査で明らかになった主要な知見には、次の事柄が含まれています。72% が「データの問題」が AI の目標達成を阻む主要因となりうると回答。68% が、AI の推進にはデータ、分析、AI を統合するプラットフォームが重要であると回答。94% が基幹業務で既に AI を利用していると回答。半数以上が 2025 年までに AI が普及すると予想。72% が「マルチクラウド」を重要と考えており、戦略的な柔軟性を維持するという目的で、多くが「オープンスタンダード」を支持。レポートをダウンロード製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.プライバシー通知\|利用規約\|プライバシー設定\|カリフォルニア州のプライバシー権利
https://www.databricks.com/glossary/data-governance	What Is Data Governance? A Comprehensive Guide \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData GovernanceA comprehensive guide to the processes, policies and tech that organizations use to manage and get the most from their dataDownload free eBookIntroductionWhat is data governance?Data governance is a comprehensive approach that comprises the principles, practices and tools to manage an organization’s data assets throughout their lifecycle. By aligning data-related requirements with business strategy, data governance provides superior data management, quality, visibility, security and compliance capabilities across the organization. Implementing an effective data governance strategy allows companies to make data easily available for data-driven decision-making while safeguarding their data from unauthorized access, and ensuring compliance with regulatory requirements.What are the business benefits of data governance?Data governance is essential for unlocking the value of data, which is a critical asset for organizations. By implementing a robust data governance approach, businesses can leverage their data assets, gain a competitive edge, and earn and maintain customer trust by ensuring sound data and privacy practices.Increased operational efficiency and reduced costsEffective data governance allows organizations to create a single source of truth for their data estate, preventing data sprawl and silos, and reducing duplication. This leads to increased efficiency, reduced costs and easier management of security and governance concepts across the data estate.Improved productivity and faster decision-makingData governance promotes data democratization by ensuring data accuracy, consistency, and trustworthiness. It helps data users find high-quality data quickly, promoting a better understanding of the data’s meaning and context, leading to increased productivity and faster decision-making.Enhanced collaboration and value realizationA strong data governance program lays the foundation for enhanced data collaboration and sharing across teams, business units, and partners. This helps organizations promote knowledge sharing and build a better data culture, leading to increased innovation, better decision-making, and maximizing the value of their data.Enhanced security and privacyData governance mitigates security and privacy risks by implementing controls and processes to prevent unauthorized access and misuse of sensitive data. It promotes a culture of trust and transparency with stakeholders.Better compliance with regulations and standardsEffective data governance results in better compliance with regulatory requirements, such as HIPAA, FedRAMP, GDPR or CCPA. This protects the organization’s reputation, avoids potential financial and legal consequences, and increases stakeholder trust.Key elements of data governanceData catalogingEffective data governance requires knowledge of the data that exists within an organization. This is where a data catalog comes in, as it provides a centralized metadata repository for an organization’s data assets. A data catalog allows stakeholders to quickly discover, understand and access the data they need, improving data-related activities such as discovery, governance and analytics. It acts as a searchable index of all the data available, including information about its format, structure, location and usage, providing semantic value to an otherwise unidentifiable sea of information. Incorporating a data catalog into a governance program can help organizations improve their data management, enhance collaboration, reduce redundancy and ensure proper access controls and audit information retrieval. Data qualityIn today’s data-driven world, ensuring high data quality is crucial for accurate analytics, informed decision-making and cost-effectiveness. Data quality directly impacts the reliability of data-driven decisions and is a key aspect of data governance. To maintain effective data governance, organizations must prioritize the evaluation of key data quality attributes such as accuracy, completeness, freshness and compliance with data-quality rules. Therefore, a strong focus on data quality is essential in any data governance strategy, as it helps trace data lineage, enforce data quality rules, and track changes. Don’t let poor data quality compromise your business decisions and resource allocation — prioritize data quality as a critical part of your data governance efforts for better outcomes. Data classification Data classification is a crucial part of data governance that involves organizing and categorizing data based on its sensitivity, value and criticality. With the exponential growth of data, businesses are increasingly concerned about protecting sensitive data, mitigating risks and ensuring data quality. Classification allows organizations to identify and classify data based on its risk level and importance, allowing them to apply appropriate security measures and policies. A robust data classification system enhances data governance, reduces risks and ensures data quality and protection at scale. Data securityOrganizations understand the significance of granting high-quality data access to their teams to drive insights and business value, while prioritizing sensitive data protection against unauthorized access. Effective data access management is crucial for data security and governance, and a good data security governance program should include access controls that define which groups or individuals can access what data. These controls can be highly specific, down to the individual record or file. As data breaches and regulations such as GDPR and CCPA pose increased risks, businesses must establish clear governance policies that define who can access sensitive data sets and how to track any misuse. Unauthorized access to private or sensitive information should not occur, and implementing effective access management strategies is essential to safeguard data and maintain customer trust. Auditing data entitlements and accessEffective data access auditing is a critical aspect of data governance and security governance programs, particularly in regulated industries. By understanding who has access to what data and tracking recent access, organizations can proactively identify overentitled users or groups and adjust their access accordingly, minimizing the risk of data misuse. Without proper audit mechanisms in place, an organization may not be fully aware of their risk surface area, leaving them vulnerable to data breaches and regulatory noncompliance. Therefore, a well-designed audit team within a data governance or security governance organization plays a key role in ensuring data security and compliance with regulations such as GDPR and CCPA. By implementing effective data access auditing strategies, organizations can maintain the trust of their customers and protect their data from unauthorized access or misuse. Data lineageData lineage is a powerful tool that helps organizations ensure data quality and trustworthiness by providing a better understanding of data sources and consumption. It captures relevant metadata and events throughout the data’s lifecycle, providing an end-to-end view of how data flows across an organization’s data estate. As an essential pillar of a pragmatic data governance strategy, data lineage enables organizations to become compliant and audit-ready while reducing the operational overhead of creating audit trails manually, and providing trusted sources for audit reports. Additionally, data lineage empowers data consumers to perform better analyses, and helps data teams perform root cause analysis of any errors, significantly reducing debugging time. Data discoveryAs organizations continue to gather massive amounts of data from various sources, it’s becoming increasingly important to make this data easily discoverable for analytics, AI or ML use cases. This is critical to accelerate data democratization and unlock the true value of the data. Furthermore, with the emergence of modern data assets like dashboards, machine learning models, queries, libraries and notebooks, data discovery has become a key pillar of a robust data governance strategy. Organizations should view data discovery as a fundamental aspect of their data governance strategy. It enables data teams to easily locate data assets across the organization, collaborate on various projects, and innovate quickly and efficiently. This helps to prevent data duplication, which can be problematic as it costs money to persist them, and may lead to governance challenges at different security levels. Data sharing and collaboration Data sharing and collaboration are vital components in today’s business environment, with organizations exchanging data with internal teams, external partners, and customers across multiple clouds, data platforms and regions. As the demand for external data continues to grow, it is critical for organizations to securely exchange data while maintaining control and visibility over how their sensitive information is used. Data cleanrooms play a critical role in secure and controlled data collaboration, ensuring that data privacy regulations are upheld. It is essential for organizations to invest in open format, interoperable and multicloud data sharing technologies to meet their data-driven innovation needs. Moreover, data marketplaces serve as a bridge between data providers and consumers, facilitating the discovery and distribution of data sets. Therefore, it is crucial to recast data sharing as a business necessity and a crucial pillar of a robust data governance strategy.What does a good data governance solution look like?Data-forward organizations prioritize data, analytics and AI to drive business outcomes, and build their data strategies around a data lakehouse architecture, which unifies data, analytics and AI on a single platform. This architecture combines the best features of data warehouses and data lakes to handle all data, analytics and AI use cases. All data is stored in a cloud data lake and managed by a unified layer, allowing analytics to be performed directly on a single copy of the data. This approach simplifies data governance and security, reduces functional silos and makes collaboration easier. By instilling high trust in data, organizations can operate with confidence and better understand how data is acquired, changed, used and impacted across every analytics workload.A data governance solution for a data lakehouse provides a number of key capabilities:Centralized data catalog: A centralized data catalog stores all your data, ML models and analytics artifacts as well as metadata for each object. The unified catalog also blends in data from other catalogs such as an existing Hive metastore.Unified data access controls: A single and unified permissions model across all assets and all clouds. This includes attribute-based access control (ABAC) for personally identifiable information (PII).Data auditing: Data access is centrally audited with alerts and monitoring capabilities to promote accountability and securityData quality management: Robust data quality management with built-in quality controls, testing, monitoring and enforcement to ensure accurate and useful data is availableData lineage: Data lineage to get end-to-end visibility into how data flows in the lakehouse, from source to consumption, down to the column levelData discovery: Easy data discovery to enable data scientists, analysts, engineers and stakeholders to quickly discover and reference relevant data and accelerate time to valueData sharing and collaboration: Data can be shared — with fine-grained access controls — across clouds, regions and platforms, preventing silos from formingData cleanrooms for privacy-safe collaboration: Collaborate on sensitive data with internal or external stakeholders in a privacy preserving environmentOpen marketplace for data, analytics and AI: Discover, access and deploy data sets, as well as AI and analytical assets — such as ML models, notebooks, applications and dashboards — without proprietary platform dependencies, complicated ETL or expensive replication.Who oversees data governance?Chief Data OfficerYour Chief Data Officer (CDO) is the most senior executive on your governance team. Ultimately, they’re responsible for your data’s security, accessibility and usability.A CDO’s role involves setting the system up, securing funding and staff for its operation (and for related aspects like tools to automate some processes), and performing regular checks on its overall status.Data ownersData owners are individuals or teams responsible for the technical administration of your data sets. They might make decisions on which team members should have access to which kinds of information. If their policies (or lack thereof) lead to a data breach, they could be held accountable.To fulfill this role and its many responsibilities, data owners are typically also senior members of your organization.Data stewardsTo assist in the day-to-day running of your data governance workflows, data owners and CDOs will appoint data stewards. Data stewardship essentially involves implementing the program that has been set out for them, and ensuring both old and new data is managed appropriately. They’re responsible for monitoring compliance from both employees and customers, and escalating issues if they arise.Data governance committeesThis committee will be the main body that creates relevant policies in your organization.Often, it will consist of senior executives and data owners, who have a keen interest in the security and usability of data. Once their policies have been approved, they may set out procedures for stewards to follow, and also resolve disputes between parties.What is the difference between data management and data governance?Effective data management and data governance are crucial for any organization that handles data. Despite the frequent interchangeable use of these terms, they have distinct differences. Data management focuses on the technical aspects of data lifecycle management, including data ingestion, integration, organization, transformation and persistence, such as backup, retrieval and archiving. In contrast, data governance is about defining organizational policies, frameworks and tools to ensure that data-related requirements are aligned with the business strategy. This includes data accuracy, consistency, compliance with regulations, and internal organizational policies as well as data quality, security, privacy, auditing and risk management. Furthermore, data governance involves defining data ownership, roles and responsibilities, and enforcing policies and procedures throughout the organization. As a key pillar of a long-term data strategy that leverages data as a strategic asset, data governance plays a significant role, while data management deals with the operational aspect of delivering on that strategy.Learn more about data governance and data sharing on DatabricksUnity CatalogData SharingDatabricks MarketplaceCleanroomsFAQWhat are the main steps of data governance?The principal steps required include:Identifying all sources of dataPreparing metadata for the data and organizing a metadata storage optionSetting up mechanisms to track data lineage for data flow and usageScanning for sensitive data in your data estateCreating a governance framework, with set policies and procedures for the various overseersChecking the framework’s compliance with relevant regulatory instrumentsPerforming data quality checks by creating a rules library that is centrally managed and versioned. Update the rules library periodically with new rules.Regularly audit data entitlements and access to ensure complianceIdentifying further risks, such as lack of data security or excess access to sensitive data setsSecuring the go-ahead from the senior executive team and data governance committeeHiring or training essential staff members, such as data stewardsEstablishing a means of data distribution, so everyone in your organization can locate the centralized data catalogHaving regular reviews with senior executives (inviting team member feedback)Constantly adapting the governance model, such as when new data sets are introducedOften, the CDO would begin creating a framework to follow these steps, with additional actors assisting them as the project grows in size.What are some basic data governance principles?Several principles are associated with sound data governance. These ideas developed in the field of data ethics and, today, many are enshrined in regulatory laws. Here are three of the most important:Accountability: This is important from two perspectives. First, you need accountability when setting up and maintaining a data governance framework. Each agent, steward and owner must know what their task is and how they can perform it. Second, if something does go wrong, there must be a clear process for holding that individual/team to account and ensuring it does not happen again.Standardization: Understanding and following regulatory laws is key to creating a successful strategy. These rules on data security and storage should be followed by businesses as standard practice to ensure your data framework may operate universally across legal jurisdictions.Transparency: Data governance has everything to do with managing other people’s data, such as your employees, clients or customers. You must make it clear to everyone what your policies are, what data is collected and why.What is at the core of data governance?As an organization, the democratization of data, analytics and AI is at the core of data governance. It’s about making data accessible — and usable — throughout your organization, without compromising on quality or security. Your clients and customers should have full confidence that their information is kept in accordance with regulations, while your teams can make the best use of all the data you’ve gathered. This blend of accessibility and security is at the heart of data governance.ResourcesKeynoteData Governance and Sharing on the Lakehouse at Data + AI Summit 2022WebinarHow to Simplify Data and AI GovernanceeBooksData, Analytics and AI GovernanceA New Approach to Secure Data SharingProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/blog/2023/02/16/announcing-new-partner-integrations-databricks-partner-connect.html	Announcing New Partner Integrations in Databricks Partner Connect - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing New Partner Integrations in Databricks Partner ConnectFive additional, validated partner solutions enhance the capabilities of your lakehouseby Riley Maris, Zaheera Valani and Maraki KetemaFebruary 16, 2023 in Platform BlogShare this postNew year, new integrations to announce! We're excited to introduce five new additions to Databricks Partner Connect– a centralized portal to help you find and integrate data, analytics, and AI solutions with your Lakehouse. We're happy to share that we've added our first partners for both the Data Governance and Data Security categories in Partner Connect! We are also continuing to add Data Ingestion, Semantic Layer and BI and Visualization partners. This reinforces our commitment to providing innovative partner solutions that extend the breadth and depth of the Databricks Lakehouse Platform through Partner Connect.Learn more about these five new integrations below!Data SecurityPrivacera Privacera is a unified Data Security Platform that integrates sensitive data discovery, masking, encryption, compliance workflow, audit, and fine-grained data access control across the Databricks Lakehouse Platform, including Unity Catalog and Databricks SQL. Privacera's new connector to Unity Catalog enables customers to manage data access, including integration with IAM solutions for attribute-based access control (ABAC), data tags for tag-based access control (TBAC), file and object level access control, dynamic row level filtering, as well as column level data access, masking, and encryption. These features enable consistent and simplified access and security policies to be applied across Databricks workspaces. Learn more about the Privacera and Databricks partnership here.Data Governanceerwin by Quest erwin by Quest provides the tools needed to help you fast-track your Databricks migration, design and optimize the lakehouse data models you employ, and efficiently catalog and govern data across multiple data platforms. Use erwin Data Modeler by Quest to auto-convert legacy data models for use in Databricks and quickly design and evolve new Lakehouse data models using market-leading data modeling capabilities like model comparison. Ingest Databricks metadata from Databricks Unity Catalog into the erwin Data Catalog to auto-document end-to-end data lineage and gain data quality visibility, impact analysis and more across your data landscape. Enrich collected metadata with business context and governance, and deliver business-friendly data discovery, data literacy and risk compliance across your organization. Learn more about using erwin by Quest here.Data IngestionHevo Data Automate and simplify your data integration process with Hevo Data. This no-code, user-friendly ELT platform helps you set up reliable data pipelines for your Databricks Lakehouse in minutes, with access to 150+ plug-and-play connectors, including popular SaaS applications, business tools, and databases. With Hevo Data, your team saves hours of engineering time and enjoys access to advanced ELT features like automated schema mapping, change data capture, post-load transformations, and more. You can now deliver data to your business team in near real-time! Sign up for a free trial today.BI and visualizationSigma Sigma is a cloud-native exploratory analytics platform with a familiar spreadsheet-like interface. Today, approximately one billion people use spreadsheets monthly. Sigma breaks down data silos and enables data teams and business analysts to align around a unified data language. Sigma leverages the Databricks SQL Driver for Go and lets users connect to the Databricks Lakehouse Platform in seconds, accelerating time to insight and removing language barriers between data and business teams. Learn more about the integration here.Semantic LayerAtScale AtScale enables smarter decision-making by accelerating the flow of data-driven insights. The AtScale semantic layer platform simplifies, accelerates, and extends business intelligence and data science capabilities for enterprise customers across all industries. With AtScale, customers are empowered to democratize data, implement self-service BI, and build a more agile analytics infrastructure for better, more impactful decision-making. Get started with AtScale on Databricks via Partner Connect, including an interactive getting-started guide available exclusively on Databricks Partner Connect. To learn more about the AtScale and Databricks partnership, watch this on-demand webinar.Customer spotlightGreenland Capital Management improves financial analysis using Sigma and Databricks in its modern data stackGreenland Capital Management, a small hedge fund, uses Sigma for its speed, scale and ease of use. One of Greenland's main decision criteria included data self-service to create live dashboards, P&L calculations, and most importantly, ensuring strong data governance across the organization. The Databricks and Sigma integration further enabled the data science team to access real-time data faster, securely, and more accurately, enabling improved financial modeling."Greenland has been thoughtful in its approach to its data stack. We needed a platform to bridge the gap between our data warehouse, our data catalog, and, ultimately, the analysis we do on a day-to-day basis. Partnering with Databricks and Sigma allowed us to organize, explore and analyze our data in order to deliver data outputs for general consumption." - Nan Xiao, Chief Technology Officer at Greenland Capital ManagementGet started with Partner ConnectSign up for a free trial of Databricks to try Partner Connect at no additional cost, and keep an eye out as we unveil more integrations in the coming months.Try Databricks for freeGet StartedRelated postsLaunching dbt Cloud in Databricks Partner ConnectApril 14, 2022 by Bilal Aslam, Hiral Jasani, Shant Hovsepian, Dave Eyler, Daniel Rosenthal and Bemnet Merha in Partners We are delighted to announce that dbt Cloud, the fastest and most reliable way to build, manage and monitor dbt projects, is now... Build Your Business on Databricks With Partner ConnectNovember 18, 2021 by Dave Eyler, Pankaj Dugar and Zaheera Valani in Platform Blog At Databricks we believe that to create the ultimate customer experience, we must leverage the work of more than just our employees and... Announcing New Partner Integrations in Partner ConnectJune 15, 2022 by Hiral Jasani, Bilal Aslam, Zaheera Valani and Katie Cummiskey in Company Blog We are excited to announce six new integrations in Databricks Partner Connect. Our expanding partnerships enable our users to integrate the freshest data... 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https://www.databricks.com/fr/company/careers	Offres d'emploi chez Databricks \| DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. 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All official communication from Databricks will come from email addresses ending with @databricks.com, @us-greenhouse-mail.io or @goodtime.io.Offres d'emploi chez DatabricksNotre mission : aider les équipes data à résoudre les problèmes les plus complexes au monde. Voulez-vous nous rejoindre ?Voir les postes ouverts OverviewCultureBenefitsDiversityStudents & new gradsFaites passer votre carrière au niveau supérieur. Misez sur l'avenir.Databricks est à la pointe de la révolution des données et de l'IA. Nous avons créé une nouvelle catégorie, le lakehouse. Et aujourd'hui, des milliers d'entreprises l'utilisent pour résoudre des problèmes comme le changement climatique, la fraude, la perte de clientèle et bien d'autres encore. Si vous êtes en quête d'une opportunité qui pourrait réellement marquer votre carrière, vous avez trouvé.Pourquoi l'avenir est au lakehousePourquoi choisir Databricks ?Nous nous développons rapidement et nous recrutons les meilleurs talents au monde. Nous sommes les Bricksters – uniques, intelligents, curieux et vifs. Demandez à un Brickster ce qu'il apprécie dans son travail, et vous entendrez probablement parler de notre culture.Découvrez les principes de notre culture d'entrepriseTrouvez votre équipeAdministrationDéveloppement commercialSuccès clientIngénierieIngénierie de terrainFinanceITJuridiqueMarketingOpérationsRHProduitServices professionnelsRecrutementVentesSécuritéStages et début de carrièreAvantages et travail hybridePour donner le meilleur de vous-même au travail, votre santé et votre bien-être sont essentiels. C'est pourquoi nous offrons une attractive palette d'avantages et proposons des pratiques de travail flexibles. L'important est que vous trouviez ce qui fonctionne le mieux pour vous et votre équipe.Découvrez nos avantagesDiversité, égalité et inclusionNous avons la conviction que la diversité des parcours, des perspectives et des compétences est le moteur de notre réussite. 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https://www.databricks.com/kr/solutions/data-pipelines	데이터 엔지니어링 \| DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센터웨비나 5월 18일 / 오전 8시(태평양 표준시) 안녕, 데이터 웨어하우스. 안녕하세요, 레이크하우스입니다. 데이터 레이크하우스가 최신 데이터 스택에 어떻게 부합하는지 이해하려면 참석하십시오. 지금 등록하세요솔루션산업별 솔루션금융 서비스의료 서비스 및 생명 공학제조커뮤니케이션, 미디어 및 엔터테인먼트공공 부문리테일모든 산업 보기사용 사례별 솔루션솔루션 액셀러레이터프로페셔널 서비스디지털 네이티브 비즈니스데이터 플랫폼 마이그레이션5월 9일 \| 오전 8시(태평양 표준시) 제조업을 위한 레이크하우스 살펴보기 코닝이 수동 검사를 최소화하고 운송 비용을 절감하며 고객 만족도를 높이는 중요한 결정을 내리는 방법을 들어보십시오.지금 등록하세요학습관련 문서교육 및 인증데모리소스온라인 커뮤니티University Alliance이벤트Data + AI Summit블로그LabsBeacons2023년 6월 26일~29일 직접 참석하거나 키노트 라이브스트림을 시청하세요.지금 등록하기고객파트너클라우드 파트너AWSAzureGoogle CloudPartner Connect기술 및 데이터 파트너기술 파트너 프로그램데이터 파트너 프로그램Built on Databricks Partner Program컨설팅 & SI 파트너C&SI 파트너 프로그램파트너 솔루션클릭 몇 번만으로 검증된 파트너 솔루션과 연결됩니다.자세히회사Databricks 채용Databricks 팀이사회회사 블로그보도 자료Databricks 벤처수상 실적문의처Gartner가 Databricks를 2년 연속 리더로 선정한 이유 알아보기보고서 받기Databricks 이용해 보기데모 보기문의처로그인JUNE 26-29REGISTER NOW데이터 엔지니어링매일 수천 만 개의 프로덕션 워크로드가 Databricks에서 실행시작하기데모 보기 WEBINAR • Goodbye, Data Warehouse. Hello, Lakehouse. Attend on May 18 and get a $100 credit toward a Databricks certification course Register nowDatabricks 레이크하우스 플랫폼에서 배치 및 스트리밍 데이터를 간편하게 수집하고 변환할 수 있습니다. Databricks에게 인프라의 대규모 자동 관리를 맡기고 안정적인 프로덕션 워크플로를 오케스트레이션하세요. 기본 데이터 품질 테스트 기능과 소프트웨어 개발 모범 사례 지원으로 팀 생산성을 향상할 수 있습니다.배치와 스트리밍 통합하나의 통합 API를 사용하는 단일 플랫폼을 통해 사일로를 제거하고 대규모로 배치 및 스트리밍 데이터를 수집, 변환 및 증분 처리할 수 있습니다.데이터 가치 창출에 집중Databricks가 인프라와 프로덕션 워크플로의 운영 부문을 자동으로 관리하므로 고객은 툴링이 아니라 가치 창출에 집중할 수 있습니다.원하는 도구와 연결개방적 레이크하우스 플랫폼에서 데이터 수집, ETL/ELT, 오케스트레이션에 사용하고 싶은 데이터 엔지니어링 도구를 연결하고 사용할 수 있습니다.레이크하우스 플랫폼 기반레이크하우스 플랫폼은 신뢰할 수 있는 데이터 자산을 구축 및 공유하는 데 가장 적절한 기반을 제공하며, 이러한 데이터 자산은 중앙에서 관리하고 안정적이면서도 매우 빠른 속도를 자랑합니다.“우리에게 Databricks는 모든 ETL 작업을 처리하는 원스톱 샵이 되었습니다. 레이크하우스 플랫폼을 많이 사용할수록 사용자와 플랫폼 관리자 모두에게 훨씬 편리해집니다.”— Hillevi Crognale, 엔지니어링 관리자, YipitData어떻게 작동하나요?데이터 수집 간소화자동 ETL 처리안정적인 워크플로 오케스트레이션전체적 관찰 기능 및 모니터링차세대 데이터 처리 엔진거버넌스, 안정성 및 성능의 기반데이터 수집 간소화레이크하우스 플랫폼에 데이터를 입력하고 한 곳에서 분석, AI 및 스트리밍 애플리케이션을 지원해 보세요.Auto Loader는 클라우드 스토리지에 저장되는 파일을 증분 방식으로 자동 처리하므로 상태 정보를 예약 작업이나 연속적 작업으로 관리할 필요가 없습니다. 디렉터리에서 모니터링하지 않아도 새로운 파일을 효율적으로 추적하며(수십억 개까지 확장 가능), 소스 데이터에서 스키마를 자동 추론하여 나중에 변경이 발생하면 그에 맞춰 조정합니다. COPY INTO 명령을 사용하면 애널리스트가 SQL을 통해 손쉽게 Delta Lake로 배치 파일을 수집할 수 있습니다.“데이터 엔지니어링의 생산성이 40% 향상되어서 새로운 아이디어를 개발하기까지 걸리는 시간이 며칠에서 몇 분으로 단축된 데다, 데이터 가용성과 정확성이 높아졌습니다.”— Shaun Pearce, 최고 기술 책임자, Gousto자세히자동 ETL 처리파일이 수집되고 나면 분석과 AI에 사용할 수 있도록 가공되지 않은 데이터를 변환해야 합니다. Databricks는 Delta Live Tables(DLT)로 데이터 엔지니어, 데이터 사이언티스트, 애널리스트에게 강력한 ETL 기능을 제공합니다. DLT는 간단한 선언적 방식으로 배치 또는 스트리밍 데이터를 위한 ETL 및 ML 파이프라인을 구축하는 최초의 프레임워크이며, 인프라 관리나 작업 오케스트레이션, 오류 처리, 복구와 같은 운영 복잡성과 성능 최적화를 자동화합니다. DLT를 사용하는 엔지니어는 데이터를 코드로 처리할 수 있고, 테스트, 모니터링 및 문서화 등의 소프트웨어 엔지니어링 모범 사례를 적용하여 대규모로 안정적인 파이프라인을 배포할 수 있습니다.자세히안정적인 워크플로 오케스트레이션Databricks Workflows는 모든 데이터, 분석, 레이크하우스 플랫폼에 네이티브인 AI에 대한 완전 관리형 오케스트레이션 서비스입니다. Delta Live Tables, Jobs for SQL, Spark, 노트북, dbt, ML 모델 등을 포함한 전체 수명 주기에 대해 다양한 워크로드를 오케스트레이션합니다. 기존 레이크하우스 플랫폼과 긴밀히 통합되므로 모든 클라우드에서 안정적인 프로덕션 워크로드를 생성 및 실행하면서도 최종 사용자에게 간단하게 심층적 중앙 집중형 모니터링을 제공합니다."우리의 임무는 지구에 전력을 공급하는 방식을 변화시키는 것입니다. 에너지 부문의 고객은 이러한 변화를 달성하기 위해 데이터, 컨설팅 서비스 및 연구가 필요합니다. Databricks 워크플로는 고객이 필요로 하는 인사이트를 제공할 수 있는 속도와 유연성을 제공합니다."— Yanyan Wu, 데이터 부문 부사장, Wood Mackenzie자세히전체적 관찰 기능 및 모니터링레이크하우스 플랫폼은 모든 데이터와 AI 수명 주기에 대한 가시성을 제공하므로, 데이터 엔지니어와 운영 팀에서 실시간으로 프로덕션 워크플로 상태를 확인하고, 데이터 품질을 관리하며, 과거의 트렌드를 파악할 수 있습니다. Databricks Workflows에서는 프로덕션 작업과 Delta Live Tables 파이프라인의 상태와 성능을 추적하는 데이터 플로 그래프 및 대시보드에 액세스할 수 있습니다. 이벤트 로그는 Delta Lake 테이블로 노출되어, 모든 각도에서 성능과 데이터 품질, 안정성 지표를 모니터링하고 시각화할 수 있습니다.차세대 데이터 처리 엔진Databricks 데이터 엔지니어링은 Apache Spark API와 호환되는 차세대 엔진인 Photon을 기반으로 하여 수천 개의 노드로 자동 확장하면서도 독보적인 가격 대비 성능을 제공합니다.Spark Structured Streaming은 배치 및 스트리밍 처리에 하나의 통합된 API를 제공합니다. 코드를 변경하거나 새로운 기술을 배우지 않고도 레이크하우스에서 손쉽게 스트리밍을 도입할 수 있습니다.자세히최첨단 데이터 거버넌스, 안정성 및 성능Databricks에서 데이터 엔지니어링을 사용하면 레이크하우스 플랫폼의 기본 구성 요소(Unity Catalog 및 Delta Lake)를 활용할 수 있게 됩니다. ACID 트랜잭션을 통해 안정성을 제공하고 확장 가능한 메타데이터를 매우 빠른 속도로 처리하는 오픈 소스 스토리지 형식인 Delta Lake로 가공되지 않은 데이터를 최적화합니다. 여기에 Unity Catalog를 결합하면 모든 데이터와 AI 자산에 세분화된 거버넌스를 제공할 수 있을 뿐만 아니라, 모든 클라우드에서 일관적인 데이터 탐색, 액세스, 공유 모델을 적용하여 거너번스 방식을 단순화합니다. 또한, Unity Catalog는 다른 조직과 간단하고 안전하게 데이터를 공유할 수 있는 업계 최초의 오픈 프로토콜인 Delta Sharing을 지원합니다.Databricks로 마이그레이션데이터 사일로, 느린 성능, Hadoop이나 엔터프라이즈 데이터 웨어하우스에서 발생하는 높은 비용에 지치셨나요? 모든 데이터, 분석 및 AI 사용 사례를 위한 현대적 플랫폼, Databricks 레이크하우스로 마이그레이션하세요.Databricks로 마이그레이션통합데이터 팀에 최대의 유연성을 제공할 수 있습니다. Partner Connect 및 기술 파트너 에코시스템을 활용하여 일반적으로 사용하는 데이터 엔지니어링 도구와 매끄럽게 통합해 보세요. 예를 들어 Fivetran으로 비즈니스에 중요한 데이터를 수집하고, dbt로 바로 변환하여, Apache Airflow로 파이프라인을 오케스트레이션할 수 있습니다.데이터 수집 및 ETL+ 여타 모든 Apache Spark™️ 호환 클라이언트고객 사례더 자세히 알아보기Delta Lake워크플로우Delta Live 테이블Delta Sharing관련 콘텐츠 여러분에게 필요한 모든 리소스가 한 곳에 있습니다. 리소스 라이브러리의 ebook과 동영상을 통해 Databricks에서 데이터 엔지니어링을 활용하는 장점에 대해 알아보세요. 리소스 둘러보기eBook데이터 웨어하우스의 아버지 Bill Inmon이 구축한 데이터 레이크하우스데이터, 분석 및 AI 거버넌스데이터 관리 기초데이터 엔지니어링 Big Book새로운 Delta Sharing 솔루션 알아보기왕초보를 위한 데이터 웨어하우스에서 데이터 레이크하우스로 마이그레이션이벤트Delta Live Tables로 데이터 변환 처리간편한 데이터 수집 웨비나 시리즈DATA + AI SUMMIT 2022데이터 웨어하우스의 현대화블로그Databricks Delta Live Tables(DLT) 정식 출시Databricks Workflows 소개2021년에 Databricks 및 Apache Spark용으로 개발된 새로운 구조화 스트리밍 기능 전체 개관Databricks 레이크하우스에서 반구조화된 데이터 과니를 단순화하기 위한 10가지 강력한 기능시작할 준비가 되셨나요?무료 시험판사용해 보기커뮤니티 가입AWSAzureGCP제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티솔루션산업 기준프로페셔널 서비스솔루션산업 기준프로페셔널 서비스회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처Databricks 채용 확인하기WorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/fr/company/partners/technology	Partenaires technologiques de Databricks - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai \| 8h PT Découvrez le Lakehouse pour la fabrication Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023 Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWPartenaires technologiques DatabricksInteragissez avec les partenaires technologiques Databricks pour intégrer les capacités d'ingestion de données, de business intelligence et de gouvernance à la plateforme Lakehouse de Databricks.« Avec Databricks et Fivetran, nous allons considérablement améliorer les insights marketing à l'avenir. D'un point de vue technique, les deux outils interagissent harmonieusement et l'intégration est parfaitement transparente. »– Jan-Niklas Mühlenbrock, Team Lead, Business Intelligence & ERP chez Paul HewittLes partenaires technologiques Databricks intègrent leurs solutions à Databricks pour offrir des fonctionnalités complémentaires en matière d'ETL, d'ingestion de données, de business intelligence, de machine learning et de gouvernance.Ces intégrations permettent aux clients de tirer parti de la fiabilité et de l'évolutivité de la plateforme Lakehouse de Databricks pour innover plus rapidement tout en obtenant de précieux insights de données.Contact partenairesRassemblez tous vos outils de données, d'analytique et d'IA sur une seule plateforme ouverte. Avec Partner Connect, Databricks offre un moyen rapide et facile de connecter vos outils existants à votre lakehouse à l'aide d'intégrations validées. Il vous aide aussi à découvrir et à essayer de nouvelles solutions.Devenir partenaireEn savoir plusLoading...ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterDécouvrez les offres d'emploi chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité\|Conditions d'utilisation\|Vos choix de confidentialité\|Vos droits de confidentialité en Californie
https://www.databricks.com/fr/university	Databricks University Alliance for Aspiring Data Scientists \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark™Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you’re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now“Having access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.”— Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don’t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you’re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/de/company/awards-and-recognition	Auszeichnungen und Anerkennungen \| DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse. Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt. Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai \| 8 Uhr PT Entdecken Sie das Lakehouse für die Fertigung Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023 Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWAuszeichnungen und AnerkennungenErfahren Sie, welche Anerkennung Databricks unter Branchenführern genießtLeader im Magic Quadrant for Cloud Database Management Systems 2022Customer Choice Award 2022 für Cloud-DatenbankmanagementsystemeLeader im Magic Quadrant for Cloud Database Management Systems 2021Leader im Magic Quadrant 2021 für Data Science und Machine LearningLakehouse: Hype Cycle for Data Management 2022Hot Companies to Watch in 2023Most Innovative Companies in Data ScienceThe Cloud 100The AI 50America’s Best Startup EmployersBest Workplaces in TechnologyBest Workplaces in the Bay AreaBest Workplaces for MillennialsCNBC Disruptor 50Bester Arbeitgeber 2022Möchten Sie mehr wissen?Wir würden uns freuen, Ihre Geschäftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter „Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Datenschutzhinweis\|Terms of Use\|Ihre Datenschutzwahlen\|Ihre kalifornischen Datenschutzrechte
https://www.databricks.com/de/company/newsroom	Newsroom \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNewsroomExplore articles and press releases related to Databricks news and announcementsFeatured StoriesMay 27, 2021Accidental Billionaires: How Seven Academics Who Didn’t Want To Make A Cent Are Now Worth BillionsReadMarch 2, 2023How Databricks became an A.I. sensationReadJuly 29, 2022Databricks CEO Ali Ghodsi joins CNBC's The Tech TradeReadMore HeadlinesInfoWorld, May 4, 2023Databricks acquires AI-centric Okera to aid data governance in LLMsRead nowTechCrunch, May 3, 2023Databricks acquires AI-centric data governance platform OkeraRead nowCRN, May 3, 2023Databricks Steps Up Data Governance With Okera AcquisitionRead nowVentureBeat, May 3, 2023Databricks acquires Okera to boost its AI-driven data governance platformRead nowBusiness Insider, May 3, 2023Exclusive: $38 billion data and AI darling Databricks acquires security startup OkeraRead nowLoad more articlesPress releasesMay 5, 2023Databricks plans to increase local headcount in India by more than 50% to support business growth and drive customer success; launching new R&D hub in 2023 Read nowApril 4, 2023Databricks Announces Lakehouse for Manufacturing, Empowering the World’s Leading Manufacturers to Realize the Full Value of Their DataRead nowMarch 30, 2023Databricks Announces EMEA Expansion, Databricks Infrastructure in the AWS France (Paris) RegionRead nowMarch 7, 2023Databricks Launches Simplified Real-Time Machine Learning for the LakehouseRead nowJanuary 17, 2023Databricks Strengthens Commitment in Korea, Appointing Jungwook Jang as Country ManagerRead nowSee all press releasesResourcesContactFor press inquires:[email protected]Stay connectedStay up to date and connect with us through our newsletter, social media channels and blog RSS feed.Subscribe to the newsletterGet assetsIf you would like to use Databricks materials, please contact [email protected]om and provide the following information:Your name and titleCompany name and location Description of requestView brand guidelinesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/company/partners/consulting-and-si/partner-solutions	Partner Solutions - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWPartner SolutionsPartner-developed industry and migration solutions for the lakehouseWe have partnered with leading consulting partners to build innovative solutions for industry and migration use cases. Databricks Brickbuilder Solutions are expertly designed by our partners to help you cut costs and increase value from your data. Backed by their years of industry experience — and built for the Databricks Lakehouse Platform — you can be confident that you get solutions that are tailored for your business.Search available partnerssearchPublic SectorCloud Data Migration by Accenture - DatabricksLearn moreRetail and Consumer GoodsUnified View of Demand by AccentureLearn moreAdvertising and Marketing TechnologyCPG Control Tower by AvanadeLearn moreAdvertising and Marketing TechnologyIntelligent Healthcare on Azure Databricks by AvanadeLearn moreAdvertising and Marketing TechnologyIntelligent ManufacturingLearn moreAdvertising and Marketing TechnologyLegacy System Migration by AvanadeLearn moreAdvertising and Marketing TechnologyRisk Management by AvanadeLearn moreTechnology and SoftwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksLearn moreTechnology and SoftwareMigrate to Cloud and Databricks by Capgemini and DatabricksLearn moreTechnology and SoftwareCapgemini Revenue Growth ManagementLearn moreTechnology and SoftwareMigrate to Databricks by Celebal Technologies and DatabricksLearn moreTechnology and SoftwareCognizant Video Quality of ExperienceLearn moreAdvertising and Marketing TechnologyPersona 360 by DataSentics and DatabricksLearn moreAdvertising and Marketing TechnologySAP Migration Accelerator by DataSentics - DatabricksLearn moreAdvertising and Marketing TechnologyPrecisionView™ by DeloitteLearn moreAdvertising and Marketing TechnologyTrellis by DeloitteLearn moreAdvertising and Marketing TechnologySmart Migration to Databricks by EPAMLearn moreAdvertising and Marketing TechnologyLeapLogic Migration Solution by ImpetusLearn moreLoad MoreReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/dataaisummit/speaker/celia-kung/#	Celia Kung - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCelia KungEngineering Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/ian-sotnek/#	Ian Sotnek - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingIan SotnekDirector of Product at AI Squared, IncBack to speakersIan Sotnek is co-founder and Director of Product of AI Squared, Incorporated. Ian's multidisciplinary background encompasses degrees and academic work in applied neuroscience as well as in machine learning governance and policy. This experience has prepared him to contribute to the human-computer interaction focus of AI Squared, where he leads the design and development of their open data science platform for machine learning development, governance, and integration.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/p/ebook/migrating-from-hadoop-to-data-lakehouse-for-dummies	Migrating From Hadoop to Data Lakehouse for Dummies \| DatabrickseBookMigrating From Hadoop to Data Lakehouse for DummiesLeave Hadoop behind for faster insightsHadoop platforms have failed to deliver business value due to the lack of data science capabilities, the high cost of operations and the inability to scale. As a result, enterprises are looking to migrate off of Hadoop.The Databricks Lakehouse is a cloud-native platform for all your data, analytics and AI use cases. It provides a single platform for developers, analysts, data scientists and business users, enabling them to build, deploy, scale and manage analytical applications in minutes instead of hours or days. It is built on modern, open standards and provides a common unified approach to data governance and data sharing.This book will help you discover why you should migrate from Hadoop to Databricks and how to drive business value through data science, AI and ML use cases.You’ll find out:How the lakehouse can help you meet 3 essential data and AI goals5 key steps for your migration from Hadoop to the lakehouseHow CBC Radio-Canada reduced time to insight by 50%10 steps to enable and scale your data, analytics and AI strategyGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
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https://www.databricks.com/br/solutions/industries/financial-services	Lakehouse para o setor de serviços financeirosSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernança de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePreçosMarketplaceTecnologia de código abertoCentro de segurança e confiançaWEBINAR Maio 18 / 8 AM PT Adeus, Data Warehouse. Olá, Lakehouse. Participe para entender como um data lakehouse se encaixa em sua pilha de dados moderna. Inscreva-se agoraSoluçõesSoluções por setorServiços financeirosSaúde e ciências da vidaProdução industrialComunicações, mídia e entretenimentoSetor públicoVarejoVer todos os setoresSoluções por caso de usoAceleradores de soluçãoServiços profissionaisNegócios nativos digitaisMigração da plataforma de dados9 de maio \| 8h PT Descubra a Lakehouse para Manufatura Saiba como a Corning está tomando decisões críticas que minimizam as inspeções manuais, reduzem os custos de envio e aumentam a satisfação do cliente.Inscreva-se hojeAprenderDocumentaçãoTreinamento e certificaçãoDemosRecursosComunidade onlineAliança com universidadesEventosData+AI SummitBlogLaboratóriosBeaconsA maior conferência de dados, análises e IA do mundo retorna a São Francisco, de 26 a 29 de junho. ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConexão de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSoluções para parceirosConecte-se com apenas alguns cliques a soluções de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de AdministraçãoBlog da empresaImprensaDatabricks VenturesPrêmios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como líder pelo segundo ano consecutivoObtenha o relatórioExperimente DatabricksAssista às DemosEntre em contatoInício de sessãoJUNE 26-29REGISTER NOWLakehouse para o setor de serviços financeirosImpulsionando instituições de serviços financeiros orientadas a dados e IA do futuroComece agoraAgendar uma demonstraçãoO quatro desafios de dados no setor de serviços financeirosGovernança e gerenciamento de dados A falta de agilidade dos dados e reprodutibilidade do modelo dificulta o cumprimento dos requisitos regulatórios específicos dos serviços financeiros.Insights mais profundos dos clientes Os silos de dados impedem ter uma visão completa dos comportamentos dos clientes, das oportunidades de vendas cruzadas e dos insights necessários para hiperpersonalização em escala.Decisões em tempo real Ferramentas isoladas e restritas ao fornecedor dificultam a capacidade de realizar análises em tempo real que impulsionam e democratizam decisões financeiras mais inteligentes.Acesso a dados de terceiros As tecnologias legadas não podem aproveitar os insights financeiros e de clientes de conjuntos de dados não estruturados e alternativos que estão se desenvolvendo rapidamente. Elas também não oferecem recursos de compartilhamento de dados abertos para promover a colaboração.Lakehouse para o setor de serviços financeirosPlataforma unificada de dados e IA Uma plataforma única que reúne todas as suas cargas de trabalho de dados e análises para permitir inovações profundas para instituições de serviços financeiros modernas. Soluções para parceiros Os principais provedores de soluções do mundo usam o lakehouse para o setor de serviços financeiros. Aproveite as ofertas predefinidas que aceleram a transformação orientada por dados. Ferramentas para acelerar os resultados dos negócios A Databricks e seus parceiros criaram uma variedade de aceleradores de soluções que ajudam a lidar com casos comuns de uso de serviços financeiros, desde investimentos ESG até prevenção de fraudes. Colaboração no setor Permita o compartilhamento seguro e aberto de dados por meio do nosso ecossistema de dados, incluindo S&P Global, Intercontinental Exchange, FactSet e Nasdaq, para liberar inovações que impulsionam a criação de valor sustentável. Transformação dos serviços financeiros com Lakehouse “A visão da Nasdaq para dados e IA é alimentada pelo Databricks Lakehouse. Usamos essa solução para processar grandes quantidades de dados financeiros e alternativos complexos a fim de criar dados e insights para nossos clientes. Além disso, a Databricks desempenha um papel importante em nossos esforços de modernizar a entrega e o consumo de dados. A Databricks nos permite enviar dados diretamente para workspaces analíticos, para que nossos clientes possam analisar e integrar dados críticos rapidamente sem precisar mover terabytes.”— Bill Dague, Head do Nasdaq Data Link, NasdaqPor que lakehouse para o setor de serviços financeiros? Reúna dados e IA em uma plataforma aberta e colaborativa que ajuda você a minimizar riscos, proporcionar experiências ricas aos clientes e acelerar a inovaçãoAbordagem de governança para conformidade e gerenciamento de riscos Simplifique a complexidade dos relatórios regulatórios, gerenciamento de riscos e conformidade, otimizando com segurança a aquisição, o processamento e a transmissão de dados para implementar as melhores práticas de governança.Produtos e serviços personalizados Reúna uma variedade de dados — de dados de mercado a dados alternativos — para experiências hiperpersonalizadas que geram oportunidades de vendas cruzadas, satisfação do cliente e aumento de share of wallet.Insights em tempo real, decisões mais inteligentes Ingira rapidamente todas as suas fontes de dados em escala para tomar melhores decisões de investimento, detecte rapidamente novos esquemas de fraude e traga recursos em tempo real para práticas de gerenciamento de riscos.Monetização e compartilhamento de dados abertos Reúna grandes quantidades de dados internos e de terceiros para compartilhar soluções financeiras inovadoras, monetizar novos produtos de dados e entregar recursos analíticos avançados para qualquer nuvem ou ferramenta sem se prender a tecnologias proprietárias.Baixar e-bookParceiros e soluçõesMude para formatos abertos e padronização de dados para análises e IAGerenciamento de riscosImplemente dados rapidamente em modelos de valor em risco para identificar riscos emergentes e possíveis ameaças.IntroduçãoModernização de cartões obsoletos e portfólios de serviços bancários principaisPermita a conversão rápida de sistemas externos e obtenha uma capacidade de conversão totalmente configurável e industrializada.IntroduçãoPersona 360Crie perfis de clientes completos e unificados em um modelo de dados inteligente.IntroduçãoVer todas as soluções de parceirosSegurança cibernética em grande escalaDetecte ameaças rapidamente, investigue seu impacto e reduza os riscos com o Splunk e DatabricksIntroduçãoClassificação ESGTenha uma visão quantitativa da sustentabilidade e garanta que as empresas sejam responsáveis por suas açõesIntroduçãoGerenciamento moderno de riscosAdote uma abordagem mais ágil ao gerenciamento de riscos unificando dados e IA no lakehouseIntroduçãoIdentifique fraudes com análises geoespaciais e IAUse dados geoespaciais para entender melhor os comportamentos de compra dos clientes, em termos de quem são e como fazem transações bancáriasIntroduçãoEnriquecimento de transações com classificação de comerciantesAutomatize o enriquecimento de transações para entender melhor os comportamentos dos clientes e impulsionar a hiperpersonalizaçãoIntroduçãoModelos de IA baseados em regras para combater fraudes financeirasModernize as estratégias de prevenção contra fraudes para reduzir custos operacionais e aumentar a confiança dos clientesIntroduçãoTransmissão oportuna e confiável de relatórios regulatóriosCombine modelos de dados do setor de serviços financeiros com a nuvem para permitir altos padrões de governança com custos de desenvolvimento reduzidosIntroduçãoModernização das plataformas de dados de investimentoUse todo o poder dos dados do mercado financeiro para se concentrar na entrega de produtos aos clientesIntroduçãoCombate à lavagem de dinheiro (AML)Habilite casos de uso com IA, como fuzzy match e análise de imagens, para combater a lavagem de dinheiro e o financiamento do terrorismoIntroduçãoVer todas as soluçõesLakehouse para o setor de serviços financeiros na práticaSucesso conjunto: Como dados e IA impulsionam a colaboração no lakehouseParticipe →Recursos Todos os recursos de que você precisa. Reunidos em um só lugar. Explore nossa biblioteca de recursos: você encontrará e-books e vídeos sobre dados e IA para o setor de serviços financeiros. Explorar recursose-books e infográficos[Infográfico] Dados para ancorar uma nova era de gestão de riscosSaiba como aproveitar facilmente os benefícios dos dados e da IA no setor de serviços financeirosAproveitamento de dados alternativos e de terceiros em serviços financeirosTornar o ESG uma realidade com análise de dados e IA Prevenção de fraudes com dados + IA: uma cartilha para ameaças modernas Vídeos e downloadsMetodologias de investimento ESG explicáveis e transparentesSegurança cibernética no setor de serviços financeirosAceleramento a inovação orientada por dados e IA no setor de serviços financeirosAnálise ESG: vídeo explicativoModernização do gerenciamento de riscosPlataformas de investimento modernas com lakehouse para o setor de serviços financeirosFolha de solução do Industry Lakehouse BlueprintsBlogsAcelerador para bancos e fintechs que usam transações com cartão de créditoUma abordagem orientada por dados para o meio ambiente, questões sociais e governançaConstrução de uma plataforma moderna de gerenciamento de risco de serviços financeirosUso de seus dados para impedir fraudes com cartões de crédito: Capital One e outras práticas recomendadasEstratégias de modernização de plataformas de dados de investimentoMelhore a experiência do cliente por meio do enriquecimento de transações Destaques Data + AI Summit 2022 para o setor de serviços financeirosLakehouse para o setor de serviços financeirosTudo pronto para começar?Adoraríamos saber sobre seus objetivos de negócios. Nossa equipe de serviços fará todo o possível para ajudar sua empresa a ter sucesso.Experimente o Databricks gratuitamenteAgendar uma demonstraçãoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Aviso de privacidade\|Termos de Uso\|Suas opções de privacidade\|Seus direitos de privacidade na Califórnia
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Databricks may take certain steps to verify your request using information available to us, such as your email address or other information associated with your Databricks account, and if needed we may ask you to provide additional information for the purposes of verifying your request. Any information you provide to us for verification purposes will only be used to process and maintain a record of your request.As described above, we may also process personal information that has been submitted by a Customer to our Platform Services. If your personal information has been submitted to the Platform Services by or on behalf of a Databricks Customer and you wish to exercise your privacy rights, please direct your request to the relevant Customer. For other inquiries, please contact us at [email protected].Additional Information for Certain JurisdictionsThis section provides additional information about our privacy practices for certain jurisdictions.CaliforniaIf you are a California resident, the California Consumer Privacy Act (“CCPA”) requires us to provide you with additional information regarding your rights with respect to your “personal information. This information is described in our Supplemental Privacy Notice to California Residents. Other US StatesDepending on applicable laws in your state of residence, you may request to: (1) confirm whether or not we process your personal information; (2) access, correct, or delete personal information we maintain about you; (3) receive a portable copy of such personal information; and/or (4) restrict or opt out of certain processing of your personal information, such as targeted advertising, or profiling in furtherance of decisions that produce legal or similarly significant effects. If we refuse to take action on a request, we will provide instructions on how you may appeal the decision. We will respond to requests consistent with applicable law.European Economic Area, UK and SwitzerlandIf you are located in the European Economic Area, United Kingdom or Switzerland, the controller of your personal information is Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, United States. We only collect your personal information if we have a legal basis for doing so. The legal basis that we rely on depends on the personal information concerned and the specific context in which we collect it. Generally, we collect and process your personal information where:We need it to enter into or perform a contract with you, such as to provide you with the Platform Services, respond to your request, or provide you with customer support;We need to process your personal information to comply with a legal obligation (such as to comply with applicable legal, tax and accounting requirements) or to protect the vital interests of you or other individuals;You give us your consent, such as to receive certain marketing communications; orWhere we have a legitimate interest, such as to respond to your requests and inquiries, to ensure the security of the Sites and Platform Services, to detect and prevent fraud, to maintain, customize and improve the Sites and Platform Services, to promote Databricks and our Platform Services, and to defend our interests and rights.If you have consented to our use of your personal information for a specific purpose, you have the right to change your mind at any time but this will not affect our processing of your information that has already taken place. You also have the following rights with respect to your personal information:The right to access, correct, update, or request deletion of your personal information;The right to object to the processing of your personal information or ask that we restrict the processing of your personal information;The right to request portability of your personal information;The right to withdraw your personal information at any time, if we collected and processed your personal information with your consent; andThe right to lodge a complaint with your national data protection authority or equivalent regulatory body.If you wish to exercise any of your rights under data protection laws, please contact us as described under “Your Choices and Rights”.Other Important InformationNotice to Authorized UsersOur Platform Services are intended to be used by organizations. Where the Platform Services are made available to you through an organization (e.g., your employer), that organization is the administrator of the Platform Services and responsible for the accounts and/or services over which it has control. For example, administrators can access and change information in your account or restrict and terminate your access to the Platform Services. We are not responsible for the privacy or security practices of an administrator's organization, which may be different from this Privacy Notice. Please contact your organization or refer to your organization's policies for more information.Data RetentionDatabricks retains the personal information described in this Privacy Notice for as long as you use our Databricks Services, as may be required by law (for example, to comply with applicable legal tax or accounting requirements), as necessary for other legitimate business or commercial purposes described in this Privacy Notice (for example, to resolve disputes or enforce our agreements), or as otherwise communicated to you.SecurityWe are committed to protecting your information. We use a variety of technical, physical, and organizational security measures designed to protect against unauthorized access, alteration, disclosure, or destruction of information. However, no security measures are perfect or impenetrable. As such, we cannot guarantee the security of your information.Third Party ServicesOur Databricks Services may contain links to third party websites, applications, services, or social networks (including co-branded websites or products that are maintained by one of our business partners). We may also make available certain features that allow you to sign into our Sites using third party login credentials (such as LinkedIn, Facebook, Twitter and Google+) or access third party services from our Platform Services (such as Github). Any information that you choose to submit to third party services is not covered by this Privacy Notice. We encourage you to read the terms of use and privacy notices of use of such third party services before sharing your information with them to understand how your information may be collected and used.Children's DataThe Sites and Platform Services are not directed to children under 18 years of age and Databricks does not knowingly collect personal information from children under 18. If we learn that we have collected any personal information from children under 18, we will promptly take steps to delete such information. If you are aware that a child has submitted us such information, please contact us using the details provided below.Changes to this NoticeDatabricks may change this Privacy Notice from time to time. We will post any changes on this page and, if we make material changes, provide a more prominent notice (for example, by adding a statement to the website landing page, providing notice through the Platform Services login screen, or by emailing you). You can see the date on which the latest version of this Privacy Notice was posted below. If you disagree with any changes to this Privacy Notice, you should stop using the Databricks Services and deactivate your Databricks account. How to Contact UsPlease contact us at [email protected] if you have any questions about our privacy practices or this Privacy Notice. You can also write to us at Databricks Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105 Attn: Privacy.If you interact with Databricks through or on behalf of your organization, then your personal information may also be subject to your organization’s privacy practices and you should direct any questions to that organization.Last updated: January 3, 2023ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/dataaisummit/speaker/jeffrey-hess	Jeffrey Hess - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeffrey HessLead Technologist at Booz Allen HamiltonBack to speakersJeff is a Lead Technologist at Booz Allen Hamilton responsible for standardizing enterprise data environments and has led multiple large-scale transformation projects to help stakeholders make the most of their data. Jeff oversees the entire data ecosystem, from moving and storing data, transforming and prepping data, visualizing data, and securing data. Jeff began as a business intelligence developer and continued to grow his passion for analytics, leading to a diverse skillset that sets his clients up for success.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/legal/us-pub-sector-services	Public Sector Services Schedule \| DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPublic Sector Services ScheduleThis Schedule sets forth terms related to use by Public Sector Customers of Databricks Services and is incorporated as part of the Master Cloud Services Agreement (the “MCSA”). The MCSA and this Schedule, together with any other Schedules that reference or are otherwise incorporated into the MCSA, and any accompanying or future Order you enter into with Databricks issued under the MCSA, comprise the Agreement. This Schedule will co-terminate with the MCSA. Capitalized terms used but not defined in this Schedule have the meaning assigned to them in the MCSA.Contracting Entity and Order of Precedence. If an Order identifies the Databricks contracting party as Databricks Federal, LLC (“DBF”), then any references in the Agreement to Databricks, including those contained in this Schedule, will be deemed to refer to DBF. Orders referencing DBF or any Order between Databricks and a Public Sector Customer will be deemed to incorporate this Schedule. In the event of a conflict between this Schedule and the MCSA or another Schedule thereto, this Schedule will be deemed to control solely for such DBF Order or other Public Sector Order.Databricks Services. This Schedule establishes the terms and conditions enabling Databricks to provide Databricks Services to Public Sector Customers. For the purposes of this Schedule, references to “Customer” in an Order, the MCSA or any Schedule thereto will be deemed to refer to Public Sector Customer or Customer Representative, as applicable. This Schedule does not grant you access to the Databricks Services without mutual agreement to an Order and applicable Databricks Services Schedule.Additional Definitions.“Customer Information” means Customer Content (if you are purchasing Platform Services) and / or Customer Materials (if you are purchasing Advisory Services).“Customer Representative” means an organization authorized on behalf of a Public Sector Customer to purchase Databricks Services on its behalf, as designated in an applicable Order.“Federal Customer” means any United States federal government branch or agency Customer of Databricks Services subject to this Schedule, including agencies and departments from the Executive Branch, the Congress, or the Military.“Public Sector Customer” means any Federal Customer or other United States state or local government, or entity, authority, agency, or body exercising executive, legislative, judicial, regulatory or administrative functions of any such government, who purchases Databricks Services subject to this Schedule. Public Sector Customer(s) may include public universities and hospitals.Modification. Notwithstanding anything contained in the MCSA or any other Schedule, you agree as follows: U.S. Government License Rights. If Customer is a Federal Customer, or the Agreement otherwise become subject to the Federal Acquisition Regulation (FAR), Customer acknowledges and agrees that the Platform Services (including PVC Services, as applicable), Support Services (as applicable), and accompanying documentation constitute “commercial computer software” and “commercial computer software documentation”, respectively, provided as “Commercial Items” as defined in FAR 2.101. The Platform Services (including PVC Services, as applicable), Support Services (as applicable), and accompanying documentation have been developed solely at private expense, and as set forth in FAR 12.212 and DFARS Section 227.7202, any use, modification, reproduction release, performance, display or disclosure thereof shall be solely in accordance with the terms of the MCSA as modified by this Schedule.Customer Representative Obligations. Customer Representative will have no rights to the Databricks Services if purchasing Databricks Services on behalf of a Public Sector Customer except to the extent that a Public Sector Customer provides access to Customer Representative as its Authorized User. Customer Representative agrees to bind Public Sector Customer to the terms of the Agreement, including this Schedule, and will ensure that Databricks will be a third party beneficiary to such agreement. Customer Representative acknowledges that submission of a purchase order or Order will be deemed to be a representation to Databricks that the applicable Public Sector Customer has assented to the terms of the Agreement. Customer Representative will use commercially reasonable efforts to enforce the terms of the Agreement in the event it becomes aware that the Public Sector Customer has breached any terms and conditions of the Agreement where such breach adversely affects Databricks’ rights or contractual protections. Customer Representative will notify Databricks promptly upon learning of any such breach.Acceptance. Any Advisory Services or Training Services provided under the MCSA shall be deemed accepted upon delivery.Confidentiality. Any provisions contained in the Agreement that require a Public Sector Customer to keep certain information confidential may be subject to the Freedom of Information Act, 5 U.S.C. §552 or similar applicable state or local state law, and any order by a United States Federal Court or court of appropriate jurisdiction.Equitable Relief. Orders entered into directly with Databricks by a Federal Customer subject to this Schedule will only allow equitable relief when explicitly provided by statute (e.g., Prompt Payment Act or Equal Access to Justice Act).Auto Renewal, Customer Responsibility, and Indemnification. If you are a Federal Customer subject to the Anti-Deficiency Act or similar limitations on fees or payment absent approved allocation of funding, any auto-renewal of Databricks Services, penalty fees or interest accrual associated with late payment, or Customer indemnification obligations in the Agreement will be deemed inapplicable. Federal Customer agrees to be responsible to Databricks for any claim (i) by a third party alleging that Customer Information or its use with the Databricks Services infringes or misappropriates such party’s Intellectual Property Rights; and / or (ii) arising from or related to your use of the Databricks Services allegedly in violation of any applicable law or the Agreement. Any clause in the Agreement requiring Databricks to defend or indemnify a Public Sector Customer is hereby amended solely to the extent that (a) the U.S. Department of Justice has the sole right to represent the Federal Customers in any such action in accordance with 28 U.S.C. 516, and (b) representation on behalf of Public Sector Customers may lie solely with the applicable state attorney general’s office if you are a state or local government entity.Governing Law. Orders entered into directly by a Federal Customer subject to this Schedule, the MCSA and any other applicable Schedules will be governed by and construed in accordance with the laws of the United States, and venue and jurisdiction of any dispute will be determined by applicable federal statute. If the federal laws of the United States are not dispositive, then to the extent permitted by federal law, the Agreement will be governed by the laws of the State of California, excluding its conflict of law principles. If you are a state or local government entity, the Agreement is governed by the laws of your state, excluding its conflict of laws principles. In the event the Uniform Computer Information Transactions Act (UCITA) or any similar laws or regulations are enacted, to the extent allowed by law, such law or regulation will not apply to the Agreement, and the governing law will remain as if such law or regulation had not been enacted. The Agreement does not affect statutory rights that cannot be waived or changed by contract.Disputes. Notwithstanding any other provision in the Agreement, any dispute between Databricks and any Federal Customer arising under or related to the Agreement will be resolved exclusively under the terms and procedures of the Contract Disputes Act (41 U.S.C. Chapter 71).Assignment. If you are a Federal Customer purchasing directly from Databricks, then except to the extent transfer may not be legally restricted, you may not assign the Agreement, any Order, or any right or obligation under the Agreement, or delegate any performance, without Databricks’ prior written consent, which consent will not be unreasonably withheld. Databricks may assign its right to receive payment in accordance with the Assignment of Claims Act (31 U.S.C. 3727) and FAR 52.212-4(b), and may assign the Agreement to the extent not prohibited by the Anti-Assignment Act (41 U.S.C. 15). Subject to the requirements of FAR 42.12 (Novation and Change-of-Name Agreements), you agree to recognize Databricks’ successor in interest following a transfer of assets or a change in name. Any attempted assignment or transfer in violation of the foregoing will be void. Subject to the foregoing, the Agreement will be binding upon and will inure to the benefit of the parties and their respective successors and assigns.Taxes. References to taxes payable by Customer will not apply to your purchases of Databricks Services to the extent You are exempt from such taxes, provided that you agree to provide documentation reasonably acceptable to Databricks evidencing your tax-exempt status.Last Updated August 12, 2022. For earlier versions, please send a request to [email protected] (with “TOS Request” in the subject).ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. 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https://www.databricks.com/company/careers/open-positions?location=san%20francisco%2C%20california	Current job openings at Databricks \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/kr/company/partners/consulting-and-si/candsi-partner-program	파트너 페이지: 컨설팅 및 SI 파트너 \| DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센터웨비나 5월 18일 / 오전 8시(태평양 표준시) 안녕, 데이터 웨어하우스. 안녕하세요, 레이크하우스입니다. 데이터 레이크하우스가 최신 데이터 스택에 어떻게 부합하는지 이해하려면 참석하십시오. 지금 등록하세요솔루션산업별 솔루션금융 서비스의료 서비스 및 생명 공학제조커뮤니케이션, 미디어 및 엔터테인먼트공공 부문리테일모든 산업 보기사용 사례별 솔루션솔루션 액셀러레이터프로페셔널 서비스디지털 네이티브 비즈니스데이터 플랫폼 마이그레이션5월 9일 \| 오전 8시(태평양 표준시) 제조업을 위한 레이크하우스 살펴보기 코닝이 수동 검사를 최소화하고 운송 비용을 절감하며 고객 만족도를 높이는 중요한 결정을 내리는 방법을 들어보십시오.지금 등록하세요학습관련 문서교육 및 인증데모리소스온라인 커뮤니티University Alliance이벤트Data + AI Summit블로그LabsBeacons2023년 6월 26일~29일 직접 참석하거나 키노트 라이브스트림을 시청하세요.지금 등록하기고객파트너클라우드 파트너AWSAzureGoogle CloudPartner Connect기술 및 데이터 파트너기술 파트너 프로그램데이터 파트너 프로그램Built on Databricks Partner Program컨설팅 & SI 파트너C&SI 파트너 프로그램파트너 솔루션클릭 몇 번만으로 검증된 파트너 솔루션과 연결됩니다.자세히회사Databricks 채용Databricks 팀이사회회사 블로그보도 자료Databricks 벤처수상 실적문의처Gartner가 Databricks를 2년 연속 리더로 선정한 이유 알아보기보고서 받기Databricks 이용해 보기데모 보기문의처로그인JUNE 26-29REGISTER NOWC&SI 파트너 프로그램Databricks C&SI(컨설팅 및 SI) 파트너 프로그램은 가치를 기반으로 하여, 파트너들과 더욱 긴밀히 협력하고 위대한 성과를 내도록 지원합니다.지금 신청하기공동의 고객사를 데이터 중심 기업으로 변화시키는 데이터 및 AI 서비스 제공업체로 구성된 글로벌 에코시스템에 참여해 보세요. 파트너는 다음의 영역에서 중요한 역할을 하게 됩니다.판매 효과 현장팀과 함께 레이크하우스의 비전을 홍보하고 Databricks의 입지를 확대합니다.고객 가치 플랫폼에 대한 전문성을 갖추도록 팀을 훈련시켜 사업 능력과 역량을 향상합니다.혁신 영향력이 큰 고객 사용 사례를 해결하는 반복 가능한 솔루션을 개발해 전문성을 선보입니다.참여 및 지원과 관련된 모든 혜택을 활용하여 사업을 성장시키고 성공적인 파트너십을 형성합니다.Databricks 기술 교육Databricks 레이크하우스 플랫폼 액세스기술 및 영업 지원영업 기회 등록 및 추천 수수료고객 투자 기금시장 진출 지원 및 리소스시작할 준비가 되셨나요?지금 신청하기파트너 찾기제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티솔루션산업 기준프로페셔널 서비스솔루션산업 기준프로페셔널 서비스회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처Databricks 채용 확인하기WorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark 및 Spark 로고는 Apache Software Foundation의 상표입니다.개인 정보 보호 고지\|이용약관\|귀하의 개인 정보 선택\|귀하의 캘리포니아 프라이버시 권리
https://www.databricks.com/dataaisummit/speaker/hitesh-sahni	Hitesh Sahni - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHitesh SahniHead of Cloud Data Platforms and Data Engineering Solutions at Deutsche Post DHLBack to speakersHitesh is head of Cloud Data Platforms and Solutions and Lead architect at DPDHL Group responsible for developing, scaling global cloud data management capabilities, delivering cloud data analytics projects including both data platforms and data engineering solutions. Hitesh is results oriented Technology Leader with business acumen enabling data driven digital transformation, diverse experience in Big Data Analytics and Cloud Space across various industry verticals (banking, Logistics, etc.).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/david-tempelman	David Tempelman - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDavid TempelmanResident Solutions Architect at DatabricksBack to speakersDavid is a Resident Solutions Architect at Databricks and helps customers to get most value out of their data. He has several years of experience in the Big Data and Machine Learning domain across different industries including manufacturing, retail & finance.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/beinan-wang/#	Beinan Wang - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBeinan WangSenior Staff Software Engineer at AlluxioBack to speakersDr. Beinan Wang is a Senior Staff Software Engineer from Alluxio and is the committer of PrestoDB. He is leading the engineer efforts of the next generation distributed cache. Prior to Alluxio, he was the Tech Lead of the Presto team in Twitter and he built large-scale distributed SQL systems for Twitter’s data platform. He has twelve-year experience of working on performance optimization. He received his Ph.D. in computer engineering from Syracuse University on distributed systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/br/solutions/migration	Migre para a Databricks \| DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernança de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePreçosMarketplaceTecnologia de código abertoCentro de segurança e confiançaWEBINAR Maio 18 / 8 AM PT Adeus, Data Warehouse. Olá, Lakehouse. Participe para entender como um data lakehouse se encaixa em sua pilha de dados moderna. Inscreva-se agoraSoluçõesSoluções por setorServiços financeirosSaúde e ciências da vidaProdução industrialComunicações, mídia e entretenimentoSetor públicoVarejoVer todos os setoresSoluções por caso de usoAceleradores de soluçãoServiços profissionaisNegócios nativos digitaisMigração da plataforma de dados9 de maio \| 8h PT Descubra a Lakehouse para Manufatura Saiba como a Corning está tomando decisões críticas que minimizam as inspeções manuais, reduzem os custos de envio e aumentam a satisfação do cliente.Inscreva-se hojeAprenderDocumentaçãoTreinamento e certificaçãoDemosRecursosComunidade onlineAliança com universidadesEventosData+AI SummitBlogLaboratóriosBeaconsA maior conferência de dados, análises e IA do mundo retorna a São Francisco, de 26 a 29 de junho. ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConexão de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSoluções para parceirosConecte-se com apenas alguns cliques a soluções de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de AdministraçãoBlog da empresaImprensaDatabricks VenturesPrêmios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como líder pelo segundo ano consecutivoObtenha o relatórioExperimente DatabricksAssista às DemosEntre em contatoInício de sessãoJUNE 26-29REGISTER NOWMigre para a DatabricksModernize sua plataforma de dados migrando para o Databricks Lakehouse Experimente o Databricks gratuitamenteEntre em contato com DatabricksReduza custos, inove mais rápido e simplifique sua plataforma de dados migrando para o Databricks Lakehouse a partir de seu data warehouse corporativo ou data lake legado. Agora, você pode executar todos os seus dados, funções analíticas e cargas de trabalho de IA em uma plataforma unificada moderna, baseada em padrões abertos e protegida com uma abordagem de governança comum.Por que migrar para a Databricks?Simplifique sua plataforma de dadosUse uma plataforma moderna para todos os seus casos de uso de dados, análises e IA. Unifique a governança e a experiência do usuário nas equipes de nuvem e dados. Escale de forma econômicaPare de gerenciar servidores. Escale de acordo com suas necessidades de serverless. Escale o data warehousing com desempenho até 12 vezes melhor em relação ao preço. Acelerar a inovaçãoCrie rapidamente recursos de IA, ML e análise em tempo real com ferramentas colaborativas de autoatendimento e tecnologias de código aberto, como MLflow e Apache Spark™. Migrar do Hadoop Saiba maisMigrar de um data warehouse Saiba maisMigre com confiançaAjudamos centenas de clientes a migrar de plataformas de dados legados. O uso de um processo de migração de ponta a ponta em fases fornece um modelo previsível para entender os custos durante e após a migração. E uma abordagem com foco no lakehouse para migrar todos os workloads garante suporte para casos de uso existentes e novos. O resultado é menor risco, obtenção mais rápida de valor e maior ROI.As 5 fases da migração de dadosFase 1: Descoberta Use criadores de perfil para automatizar a descoberta. Obtenha insights sobre cargas de trabalho de plataformas legadas e estime os custos de consumo da plataforma Databricks. Fase 2: Avaliação Use analisadores para uma avaliação detalhada da complexidade do código e para estimar os custos do projeto de migração. Fase 3: Estratégia Finalize o mapeamento de tecnologia e desenvolva caminhos ideais para cada migração de plataforma de origem, com orientação especializada da Databricks. Fase 4: Piloto de produção Execute um piloto com seus casos de uso e use conversores de código quando aplicável para transportar o código legado para o código compatível com a Databricks. Desenvolva um plano de implementação de migração e um plano de ação. Fase 5: Execução Repetição para todas as cargas de trabalho. Obtenha ajuda com a execução da migração e suporte de parceiros certificados ou serviços profissionais Databricks. Clientes que migraram com sucesso para a DatabricksHistória de clientePersonalizar o atendimento farmacêutico para melhorar os resultados dos pacientes Leia maisBLOG DO CLIENTEEliminar on-prem totalmente, obtendo ganhos de economia de custos e acelerando o sucesso Leia maisHistória de clienteA migração para a nuvem é necessária em uma nova era de varejo orientado a dados Leia maisSoluções BrickbuilderAproveite as soluções Brickbuilder dos principais parceiros de consultoria criadas para migrar para o Databricks LakehouseMigração de dados na nuvem pela AccentureMenos adivinhação, mais valor Comece agoraMigração do sistema legado por AvanadeMova seus dados para desbloquear seu valor total Comece agoraMigração para a nuvem e o Databricks com CapgeminiSimplifique a migração de dados para a Plataforma Databricks Lakehouse Comece agoraMigração para Databricks com Celebal TechnologiesMigração mais rápida de on-premises a um custo menor Comece agoraSolução de migração da LeapLogic com ImpetusTransforme automaticamente cargas de trabalho de ETL, data warehouse, análises e Hadoop em Databricks Comece agoraAssistente de dados para migrações Hadoop/EDW com InfosysTransfira seus dados com confiança para o Databricks Comece agoraMigração de snowflake-to-Databricks com LovelyticsGaranta um processo de migração rápido e sólido Comece agoraAcelerador de migração SAS com Tensile AISolução de migração desenvolvida pela Tensile AI e com tecnologia da Plataforma Databricks LakehouseComece agoraData Intelligence Suite com WiproMigre com confiança para o Databricks Comece agoraA sabedoria da transição para uma estratégia de data lakehouseComo uma abordagem de data lakehouse pode ajudar sua empresa a superar as limitações comuns de data warehouses e data lakesBaixarRecursose-booksMigrating From Hadoop to Data Lakehouse for DummiesLivro para leigos: Migrating from a Data Warehouse to a Data LakehouseEventosGuia passo a passo para migração do HadoopModernize seu data warehouseBlogsCinco etapas principais para uma migração bem-sucedida do Hadoop para a arquitetura de lakehouseSete motivos para migrar de seu Hadoop baseado na nuvem para a Plataforma Databricks LakehouseComece agoraA migração não precisa ser uma dor de cabeça. Entre em contato conosco hoje para conversarmos sobre como sua empresa pode proceder.Experimente o Databricks gratuitamenteEntre em contato com DatabricksProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Aviso de privacidade\|Termos de Uso\|Suas opções de privacidade\|Seus direitos de privacidade na Califórnia
https://www.databricks.com/dataaisummit/speaker/ryan-johnson/#	Ryan Johnson - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan JohnsonSenior Staff Engineer at DatabricksBack to speakersRyan Johnson is a Senior Staff Software Engineer and tech lead at Databricks, working with the Delta Lake table format at the boundary between the storage system and the query layer. Before joining Databricks, he worked on the storage layer at Amazon Redshift and previously did database systems research as a professor at the University of Toronto. He loves writing code and solving low-level systems problems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/p/ebook/improving-health-outcomes-with-data-and-ai	Improving Health Outcomes With Data and AI - DatabrickseBookImproving Health Outcomes With Data and AIHow a modern data lakehouse can help you innovate in research and patient careHealthcare and life sciences are generating more data than ever — in the form of electronic medical records, genomics and medical imaging.But data teams at leading companies, such as Regeneron, CVS Health and Sanford Health, aren’t struggling to keep up. Instead, they’re using a modern data lakehouse to harness all their data and improve patient outcomes.Read this eBook to find out how:Sanofi reduced data processing costs by 30%Biogen analyzed 2 million genomic variants in under 15 minutesRegeneron reduced data processing time from 3 weeks to 5 hoursCVS Health increased medication adherence by nearly 2%Get the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/dataaisummit/speaker/jeffrey-chou	Jeffrey Chou - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeffrey ChouCo-Founder, CEO at Sync ComputingBack to speakersJeff received his PhD in EECS from UC Berkeley as an NDSEG fellow, was a Battelle Post-Doctoral Scholar at MIT, and is an Entrepreneurial Research Fellow at Activate. Prior to Sync he was a technical staff member at MIT Lincoln Laboratory.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/br/product/data-science	Data Science \| DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernança de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePreçosMarketplaceTecnologia de código abertoCentro de segurança e confiançaWEBINAR Maio 18 / 8 AM PT Adeus, Data Warehouse. Olá, Lakehouse. Participe para entender como um data lakehouse se encaixa em sua pilha de dados moderna. Inscreva-se agoraSoluçõesSoluções por setorServiços financeirosSaúde e ciências da vidaProdução industrialComunicações, mídia e entretenimentoSetor públicoVarejoVer todos os setoresSoluções por caso de usoAceleradores de soluçãoServiços profissionaisNegócios nativos digitaisMigração da plataforma de dados9 de maio \| 8h PT Descubra a Lakehouse para Manufatura Saiba como a Corning está tomando decisões críticas que minimizam as inspeções manuais, reduzem os custos de envio e aumentam a satisfação do cliente.Inscreva-se hojeAprenderDocumentaçãoTreinamento e certificaçãoDemosRecursosComunidade onlineAliança com universidadesEventosData+AI SummitBlogLaboratóriosBeaconsA maior conferência de dados, análises e IA do mundo retorna a São Francisco, de 26 a 29 de junho. ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConexão de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSoluções para parceirosConecte-se com apenas alguns cliques a soluções de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de AdministraçãoBlog da empresaImprensaDatabricks VenturesPrêmios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como líder pelo segundo ano consecutivoObtenha o relatórioExperimente DatabricksAssista às DemosEntre em contatoInício de sessãoJUNE 26-29REGISTER NOWData ScienceData science colaborativa em escalaExperimente gratuitamenteAgendar uma demonstraçãoAprofunde-se na Ciência de Dados no DatabricksDatabricks NotebooksIDE IntegrationsReposMachine LearningSimplifique o fluxo de trabalho de data science de ponta a ponta, da preparação de dados à modelagem e ao compartilhamento de insights, com um ambiente colaborativo e unificado criado em uma fundação aberta de lakehouse. Obtenha acesso rápido a dados confiáveis, recursos de computação pré-configurados, integração de IDE, compatibilidade com várias linguagens e ferramentas de visualização avançadas integradas para flexibilidade máxima de equipes de análise de dados.Colaboração em todo o fluxo de trabalho de data scienceEscreva códigos em Python, R, Scala e SQL, explore dados com visualizações interativas e descubra novos insights com notebooks da Databricks. Compartilhe códigos com confiança e segurança com coautoria, comentários, controle automático de versões, integrações Git e controles de acesso baseados em função.Foco em data science, não em infraestruturaVocê não precisa mais se limitar à capacidade de armazenamento do seu computador ou pelo poder de processamento disponível para você. Migre rapidamente seu ambiente local para a nuvem e conecte notebooks a seus recursos de computação pessoal e clusters gerenciados automaticamente.Use sua IDE local favorita com computação escalávelA escolha de uma IDE é muito pessoal e tem grande impacto na produtividade. Conecte sua IDE favorita à Databricks para continuar aproveitando o armazenamento e a capacidade de computação ilimitados. Ou simplesmente use o RStudio ou o JupyterLab diretamente na Databricks para uma experiência tranquila.Prepare seus dados para para data scienceLimpe e catalogue todos os seus dados — em batch, streaming, estruturados ou não — em um só lugar com o Delta Lake e torne-os acessíveis a toda a sua empresa por meio de um armazenamento de dados centralizado. Quando os dados chegam, as verificações automáticas de qualidade garantem que eles atendam às expectativas e estejam prontos para análise. À medida que os dados são alimentados com novas entradas e transformações adicionais, o controle de versões ajuda você a atender às necessidades de conformidade.Ferramentas visuais com pouco código para explorar dadosUse ferramentas visuais nativas em notebooks da Databricks para preparar, transformar e analisar seus dados. Capacite equipes de todos os níveis de habilidade para trabalhar com dados. Depois que suas transformações e visualizações de dados estiverem concluídas, você pode gerar o código que é executado em segundo plano. Como não precisa mais escrever o código base, você pode dedicar mais tempo a tarefas mais produtivas.Descubra e compartilhe novos insightsCompartilhe e exporte facilmente seus resultados, transformando com rapidez suas análises em dashboards dinâmicos. Os dashboards são sempre atualizados e também podem executar queries interativas. Células, visualizações ou notebooks podem ser compartilhados com controle de acesso baseado em função e exportados em vários formatos, incluindo HTML e IPython Notebook.Migre para a DatabricksNão aguenta mais silos de dados, desempenho lento e altos custos associados a sistemas obsoletos, como Hadoop e os data warehouses corporativos? Migre para a Databricks Lakehouse: a plataforma moderna para todos os seus casos de uso de dados, análises e IA.Migre para a DatabricksRecursos Todos os recursos de que você precisa. Reunidos em um só lugar. Explore nossa biblioteca de recursos: você encontrará e-books e vídeos sobre data science e machine learning. Explorar recursosRelatórios e e-booksThe Big Book of Data ScienceThe Art of Collaborative Data Science at ScaleThe Modern Cloud Data PlatformMLflow – Uma plataforma de machine learning de código abertoExplore a nova solução de Delta SharingDatabricks nomeada líder no Gartner® Magic Quadrant™ de 2021 para as categorias DBMS e DSMLGuia de migração: Do Hadoop para DatabricksBlogsCinco etapas principais para uma migração bem-sucedida do Hadoop para a arquitetura de lakehouseEventos virtuaisGuia passo a passo para migração do HadoopTudo pronto para começar?Experimente o Databricks gratuitamenteProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Aviso de privacidade\|Termos de Uso\|Suas opções de privacidade\|Seus direitos de privacidade na Califórnia
https://www.databricks.com/dataaisummit/speaker/dipankar-mazumdar/#	Dipankar Mazumdar - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDipankar MazumdarDeveloper Advocate at DremioBack to speakersDipankar is currently a Developer Advocate at Dremio where his focus is helping data/platform engineering teams on lakehouse platform & various open-sourced projects such as Apache Iceberg & Arrow that allows data teams to apply & scale analytics. In his past roles, he worked at the intersection of Machine Learning & Data visualization. Dipankar is a co-author of the upcoming O’Reilly book on Apache Iceberg. He also holds a MS in Computer Science with research focused on ExplainableAI.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/sidharth-kunnath	Sidharth Kunnath - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSidharth KunnathPrincipal Architect at American Airlines, IncBack to speakersOver 18 years of IT experience exclusively in designing and building enterprise data analytical solutions deployed over enterprise data warehouses and data lakes, both within on-premises and cloud (Azure) Over 4 years of experience implementing data analytics projects within Azure data analytical ecosystem, leveraging Azure services like Event Hub (AEH), Stream Analytics (ASA), Azure Functions (AF), Databricks (ADB) and Azure Datalake Storage (ADLS) Experience in defining enterprise data strategy and its physical implementation across the organization Experience in Application, Solution and Data Architecture, working both with technology and the business, translating between the two Experience in implementation of real-time data streaming layer using Azure streaming architecture as well as real-time data serving layer using APIs installed over NoSQL databases like Cassandra Extensive experience implementing data warehousing projects based on Teradata Domain knowledge of airline business including subject areas like revenue management & performance, customer loyalty, flight operations, inventory, maintenance & engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/huaxin-gao/#	Huaxin Gao - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHuaxin GaoSoftware Engineer at AppleBack to speakersHuaxin Gao is an Apache Spark committer and a software engineer at Apple, focusing on Spark SQL. Prior to joining Apple, she worked on a number of SQL and ML projects at IBM.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/dilip-biswal/#	Dilip Biswal - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDilip BiswalSenior Architect at AdobeBack to speakersDilip Biswal is a Software Architect at Adobe working on Adobe Experience Platform. He is an active Apache Spark contributor and works in the open source community. He is experienced in Relational Databases, Distributed Computing and Big Data Analytics. He has extensively worked on SQL engines like Informix, Derby, and Big SQLLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/solutions/industries/media-and-entertainment	Media and Entertainment Solutions - Databricks Lakehouse - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks for Media & EntertainmentPowering the data, analytics and AI-driven future of mediaGet startedSchedule a demoFour data challenges in media and entertainmentCreating a unified audience profile Data captured, stored and managed in disparate systems prevents media organizations from having a full view of audience and advertiser data.Delivering an outstanding user experience Consumers expect frictionless 1:1 personalized experiences at all times, across their devices. The challenge is to deliver these experiences in real time, at scale.Maximizing all your media data Legacy data warehouses cannot handle unstructured data such as video, image and audio files, which prevents organizations from unlocking the full potential of their most valuable assets.Moving beyond aggregation to advanced analytics Complex AI use cases for the advertising and consumer lifecycle currently require the expensive acquisition and harmonization of massive data sets.Meet Data Lakehouse: The Best of Both Worlds in One PlatformA data lakehouse unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. It’s built on an open and reliable data foundation that efficiently handles all data types and applies one common security and governance approach across all of your data and cloud platforms.Learn moreThe lakehouse in actionLearn how the Databricks Lakehouse empowers your unique industryAdvertising & Marketing TechnologiesManage margin and add data-focused rigor to operations, improve media performance, and optimize creative to streamline work for teams.Learn moreBroadcasting & StreamingCreate personalized 1:1 experiences at scale, improve advertising performance and optimization, and derive more value from your entire content portfolio.Learn moreGamingHarness data and AI to drive better game design, improve gamer acquisition and engagement, and increase player monetization and retention.Learn moreWhy Databricks for media and entertainmentAll of your data, analytics and AI on one platform Extract the full value of your data to power breakthroughs in audience engagement, monetization and advertising optimization.Optimized for real-time Uncover actionable insights, drive 1:1 personalization and enhance your audience experience with machine learning at the core.Accelerate your business outcomes Tap Solution Accelerators that make it easy to ingest consumer data — such as clickstream engagement — and deliver on use cases like recommendation engines and multi-touch attribution.Best-in-class reliability and performance The Databricks Lakehouse offers unparalleled scale, speed and cost savings. It’s no wonder the best data warehouse is a lakehouse.Transforming media and entertainment with the lakehouse “With Databricks Lakehouse Platform on AWS, Warner Bros. Discovery is powering the future of content discovery and audience experiences. By leveraging data to better predict consumer behavior and provide personalized content recommendations in real time, we are able to customize the viewer experience and improve overall engagement for our customers.”— Martin Ma, GVP, Engineering at Warner Bros. DiscoveryExecutive insights on data, analytics and AILearn more about what other media and entertainment executives are doing to power their data strategyLearn moreWhat can you do with the lakehouse? Accelerate audience and advertiser outcomes on an open, collaborative platform for data, analytics and AI360° view of your audience Bring together all your structured and unstructured data — clickstream, demographic, social — in a single platform for analytics and AI. With a holistic view of the consumer journey, organizations can understand content preferences that help deliver more personalized experiences and develop more targeted advertising and engagement.Mitigate churn and increase ARPU With an agile cloud-based platform, organizations can quickly and reliably process massive amounts of data and feed it to downstream systems to deliver a 1:1 experience on any channel at any time. As consumers’ expectations around real-time recommendations keep rising — and media companies fight for consumer attention — ensuring that personalization approaches real time is becoming a requirement for many organizations.Drive revenue from a content library Media companies are built on unstructured data like video, images and audio files, so the ability to analyze unstructured data is essential for effective media asset management. Lakehouse for M&E can be used by marketers to leverage archived content for campaigns, production teams looking for existing content to include in new productions and sales teams seeking IP they can sell to other media companies.Leverage pre-built models for ML/AI. Put ML at the core of your business Unlock the power of machine learning to better understand consumer, employee and advertiser needs. When all your data is centralized and seamlessly connected by a full suite of collaborative analytics and machine learning tools, data teams can work together to build powerful predictive models that drive new innovations in personalization, content monetization and advertiser outcomes.Download the eBookPartners and solutions Get started with a variety of data and analytics solutions and templates specific to media and entertainment Explore our Partners PortalMulti-touch attributionMeasure ad effectiveness and optimize marketing spend with better channel attributionGet startedGamer/user toxicityFoster healthier user communities with real-time detection of toxic language and behaviorGet startedSurvival analysis/LTVPredict which consumers are at risk of churning and what factors extend the consumer lifecycleGet startedPropensity to churnEffectively manage retention, understand lifecycle and reduce your churn rateGet startedBehavioral segmentationCreate advanced segments to drive better purchasing predictions based on behaviorsGet startedSales forecasting and attributionIncrease advertising outcomes by optimizing and focusing on the best-performing channelsGet startedRecommendationsIncrease conversions and engagement with personalized omnichannel recommendationsGet startedComputer vision/LabelboxAnnotate images and videos to help drive contextual ad targeting in the Lakehouse Coming soonVideo quality of experienceAnalyze batch and streaming data to ensure a performant streaming content experienceGet startedReal-time biddingLearn how to predict ad viewability in real time to enhance your RTB strategyGet startedSee all solutionsLakehouse for Media & Entertainment in actionResources All the resources you need. All in one place. Explore the resource library to find eBooks and videos on data, analytics and AI for Media & Entertainment Explore resourceseBookDownload nowWebinarsLearn moreBlogsLearn moreReady to get started?We’d love to understand your business goals and how our services team can help you succeed.Try Databricks for freeSchedule a demoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/dataaisummit/speaker/nicolas-pelaez	Nicolas Pelaez - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNicolas PelaezTechnical Marketing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/luyang-wang	Luyang Wang - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLuyang WangLead Distinguished Scientist at VerizonBack to speakersLu is a Lead Distinguished Scientist at Verizon, where he leads a cross functional team focus on developing large scale search & recommendation services.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/michael-green/#	Michael Green - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael GreenSenior Data Scientist at Hitachi Solutions AmericaBack to speakersMichael holds a doctorate in artificial intelligence from NYU's Tandon School of Engineering. He's been researching artificial intelligence for more than 6 years, with successful projects using tree-search, evolutionary optimization, deep learning, and reinforcement learning techniques, with more than 25 peer-reviewed papers. Today, Michael works as a product manager and senior data scientist at Hitachi Solutions America, leading the AI initiative for the Empower Platform team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/customers/gousto	Customer Story: Gousto \| DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCUSTOMER STORYStreamlining food delivery fulfillment to delight customers60%Infrastructure cost reduction40%Productivity benefit for data engineering delivery99.6%End-to-end ingestion time reduction INDUSTRY: Retail and consumer goods SOLUTION: Customer retention,customer segmentation,demand forecasting,ML-based item matching,subscriber churn prediction PLATFORM USE CASE: Lakehouse,Delta Lake,data science,machine learning,ETL CLOUD: AWS“We’ve seen a 40% productivity uplift for data engineering — reducing the time it takes to develop new ideas from days to minutes and increasing the availability and accuracy of our data.” — Shaun Pearce, Chief Technology Officer, GoustoThe COVID-19 pandemic has created a demand boom for eating in and new recipe subscription services, in ways that will change consumer habits once the crisis has passed. Within this increasingly crowded field of food services, Gousto is different: They’ve always placed data at the very heart of their business to help them deliver exactly what the customer wants, every time and on time. Gousto doubled deliveries to 5 million recipe meals a month in the first half of 2020, but were held back by systems that couldn’t ingest data fast enough, couldn’t talk to each other and wouldn’t scale. Just when the pandemic exploded demand, Gousto had to temporarily stop accepting new customers. Now, with Databricks in place, Gousto is set up to achieve exciting ambitions for menu expansion, sophisticated personalization and next-day delivery.Delivery potential limited by slow data ingestion and analysisGousto’s mission is to change the way people eat through the delivery of boxes of fresh ingredients and easy-to-follow recipes. But the company is much more than a food delivery service. Gousto aims to leverage data and AI to create a more convenient and personalized experience for their customers. In the words of Gousto’s Chief Technology Officer, Shaun Pearce, “Gousto is a data company that loves food.” However, even before the massive pandemic-driven increase in demand, Gousto was at a crossroads. “We were at capacity. Demand was huge, but we couldn’t scale the fulfillment supply chain,” said Pearce.At Gousto, recipe boxes take a journey through a fulfillment center on a conveyor belt, past a series of stations where boxes stop for an agent to pack ingredients. An efficient journey means more boxes per hour. Detailed box ingredients and stock inventory data were being collected, but couldn’t be analyzed quickly enough to optimize their route or anticipate ingredient availability. The ETL batch process was taking over two hours — if it worked — meaning Gousto was always looking back at historical data and relying on ad hoc observations to make strategic decisions for the business. This latency was impacting a key performance measure — on time in full (OTIF). “We knew we had to rethink our ETL to deliver production-line data in near real-time,” said Eoin O’Flanagan, who heads up data engineering at Gousto.Added to this, Gousto had disparate systems and data sources managing warehouse stock levels and ingredient replenishment at each pick station, so it was impossible to gain a unified view into the data without significant manual effort. “The systems were not designed for querying and analytics, and we needed visibility across the whole line to make efficiency improvements,” said O’Flanagan.The time wasted on troubleshooting failed data ingest batch jobs, and maintaining infrastructure was time taken away from developing the more sophisticated data analytics. “We needed to reduce infrastructure tasks so we could focus on collaborating to write code, not dealing with pipeline and EMR issues, so that new ideas could become a reality much faster,” said O’Flanagan. Gousto needed to move from daily batch updates using costly EMR to near real-time streaming data.Optimizing recipe box fulfillment to boost conversionGousto realized they needed a cost-effective cloud-based platform on AWS that would deliver on their current challenges and ambitions for the future. With the Databricks Lakehouse Platform in place, Gousto now enjoys a coherent view of supply chain events. Merging the incoming stream of pick station inventory-level data and warehouse-stock-level data into Delta Tables in Delta Lake, using Merge and CDC, has given Gousto visibility of pick-line status refreshed in near real-time, and agents have the right ingredients on their stations to pack their assigned boxes. “Getting a near real-time view on inventory data is unlocking much more capability in our stock management, giving us a view on stock movement to the line and improved planning. We couldn’t do it without Delta Lake,” said O’Flanagan.The Databricks platform also means Gousto now has the right tooling to spin up new clusters in minutes to work on new ideas without delay. “Data preparation time has reduced from 3 hours to 5 minutes. We can easily attach notebooks to prototype new features and debug issues, collaborate on the same data, and the feedback loop for trying out new code has gone down from 20 minutes to 20 seconds,” said O’Flanagan.Running a sequence of batch jobs used to be a complex pipeline with multiple points of failure for Gousto’s data engineers, slowing their ability to feed clean data for downstream analytics to optimize their supply chain. Now, “we’ve switched off the batch pipeline, and our supply chain ETL stack is 100% streaming, with no failures since deployment,” said O’Flanagan.Serving up success with near real-time insightsGousto now enjoys near real-time reporting on fulfillment center performance and inventory levels. End-to-end ingestion time has been reduced by 99.6% — a job that took two hours is down to 15 seconds, and the ingestion infrastructure costs have been reduced. “Now we can drill down to see the reason for bottlenecks on the fulfillment line and optimize box routing and inventory slotting. It’s a proactive rather than reactive approach,” said O’Flanagan. “Which is good news for our OTIF measure, even in times of record demand,” said Pearce.The improved availability and accuracy of data mean Gousto can easily expand their customer fulfillment capacity — from two factories to four in the next year — and, as a bonus, this has also created significant infrastructure cost savings, the big one around EMR. “There’s more data running in real-time but with no increase in costs versus EMR. Like for like, it works out as a 60% cost improvement,” said O’Flanagan.In fact, because Gousto tracks ticket metrics in every development sprint, they know there’s been a 40% productivity benefit for data engineering delivery. “We have reduced the time it takes to develop new ideas from days to minutes and increased the availability and accuracy of our data,” said Pearce.Databricks is helping Gousto deliver on today’s known challenges and has Gousto ready for the unknown ones of the future — positioning the team to harness AI and ML and realize their objectives around menu personalization and next-day delivery. “Databricks has helped us take giant steps toward our ambitions. It’s a platform with a huge potential,” said Pearce.Ready to get started?Try Databricks for freeLearn more about our productTalk to an expertProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. 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https://www.databricks.com/company/careers/engineering-at-databricks	Engineering at Databricks \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWEngineering at DatabricksWork with the teams solving the world’s toughest problemsSee open jobs OverviewCultureBenefitsDiversityStudents & new gradsMake an impact with our engineering teamsAt Databricks, we believe that we win by empowering our engineering teams to iterate rapidly from idea to production. Our engineering teams constantly push the boundaries of data and AI technology — while simultaneously operating with the resilience, security and scale that are critical to making customers successful on our platform. We build highly technical products that enable data teams to solve the world’s toughest problems, from cybersecurity threat detection to cancer drug development to pioneering the next mode of transportation.Learn more about the Data Team EffectLearn more about the Databricks Lakehouse PlatformDevelop with an innovative global teamFounded in 2013 by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks has grown from a tiny corner office in Berkeley, California, to a company with employees all over the world. Databricks has since become the industry leader for data-driven decision-making with its cloud-based infrastructure, collaborative workspace, team-based version control, integrated libraries for data manipulation and visualization, Spark-compatible optimized runtime environment, and robust security. Worldwide openings There are openings in our engineering centers in San Francisco, Mountain View, Seattle/Bellevue, Amsterdam and Berlin - as well as remote opportunities worldwide - to continue our momentum. Apply todayMeet the engineers of DatabricksWhat is mentorship like at Databricks?What is the most impactful project you’ve worked on at Databricks?What is an unexpected reward you’ve experienced as an engineer?Find out what inspires our engineersTo learn more, check out our Culture Blog and Technical BlogPlatform EngineeringThe platform teams are responsible for datacenter-scale infrastructure with millions of virtual machines under management, supporting hundreds of thousands of customers. These teams build scalable infrastructure for building, deploying, monitoring and operating fleets of services across multiple cloud platforms (AWS, GCP and Azure). Areas of focus include the core application architecture, distributed systems, networking, security and API infrastructure.Core Storage and Data ProcessingData Science ApplicationsSee open jobsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/blog/2019/11/20/azure-databricks-highlights-adoption-of-delta-lake-mlflow-and-integration-with-azure-machine-learning-at-microsoft-ignite-2019.html	Azure Databricks Momentum at Microsoft Ignite 2019Skip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAzure Databricks Highlights Adoption of Delta Lake, MLflow, and Integration with Azure Machine Learning at Microsoft Ignite 2019by Abhinav Garg and Clinton FordNovember 20, 2019 in Company BlogShare this postAt Microsoft Ignite 2019, thousands of attendees participated in hands-on workshops, breakout sessions, and theater presentations to learn how customers are achieving phenomenal results with Azure Databricks! It was an action-packed week of making new connections and learning about new innovation across data science, data engineering, and business analytics. We shared the news that over 75% of data processed on Azure Databricks is in Delta Lake -- the new open source standard for data lakes. Hands-on labs and breakout sessions gave attendees an opportunity to see and experience Delta Lake on Azure Databricks first hand. Delta Lake’s openness and extensibility enable faster innovation and more effective use of data. Azure Databricks has seen amazing growth over the past two years. This rapid growth has created the need for new tools and capabilities such as the MLflow Model Registry and ML lifecycle management which help customers track, deploy, and update their ML models. Attendees learned three ways Azure Databricks works with Azure Synapse Analytics to bring analytics, business intelligence (BI), and data science together in one solution architecture. Azure Databricks momentum and acceleration were highlighted in many sessions during the week of Ignite 2019. Below are just a few sessions to give you an idea of the breadth of customer use cases driving such phenomenal growth. Azure Databricks Sessions at Ignite 2019Delta Lake on Azure Databricks: Implementing a new open source standard for Data Lakes (THR2339) - Ajay Singh from Databricks shared how you can enhance your data lakes for greater value by adding new capabilities for transactions, version control and indexing using the latest open source innovations. Founded by the original creators of Apache Spark, Databricks has continued to innovate by launching a new open source project called Delta Lake designed to make existing data lakes more scalable and reliable. Built on top of infinitely scalable Azure Data Lake Storage and deeply integrated with Azure SQL Data Warehouse, Delta Lake on Azure Databricks makes data better prepared for analytic and machine learning workloads. Available today as part of Azure Databricks, see why large organizations are upgrading their data lake in-place with zero migration to Delta Lake!Managing your ML lifecycle with Azure Databricks and Azure Machine Learning (BRK3245) - Premal Shah from Microsoft and Mike Cornell from Databricks shared how machine learning development has new complexities beyond software development. There are a myriad of tools and frameworks which make it hard to track experiments, reproduce results, and deploy machine learning models. Learn how you can accelerate and manage your end-to-end machine learning lifecycle on Azure Databricks using MLflow and Azure ML to reliably build, share, and deploy machine learning applications using Azure Databricks.Hands-on with Azure Databricks Delta Lake (WRK2013) - In this lab, Kyle Weller, Premal Shah, Shiva Nimmagadda Venkata, and Santosh Perla from Microsoft guided attendees as they learned how to increase performance and reliability of their data engineering pipelines with Azure Databricks Delta Lake. Delta Lake provides optimized layouts to enable big data use cases, from batch and streaming ingests, fast interactive queries, to machine learning.Maximizing your Azure Databricks deployment (BRK3043) - Yatharth Gupta from Microsoft shared insights and key steps to get the most out of your Azure Databricks resources. Whether you’re new to Spark or an Azure Databricks veteran, attend and learn the tips, tricks, and best practices for working with Azure Databricks. Based on experiences with real industry customers, these best practices cover deployments, management, security, networking, monitoring, machine learning, and more. See how the power of Azure Databricks’ managed Spark experience can benefit your analytics pipeline!Azure Databricks and Azure Machine Learning better together (THR2186) - In this theater session, Premal Shah from Microsoft demonstrated the new integrations between Azure Databricks and Azure Machine Learning to realize comprehensive E2E machine learning scenarios for our customers.Data reproducibility, audits, immediate rollbacks and other applications of time travel with Delta Lake in Azure Databricks (BRK3254) - Time travel is now possible with Azure Databricks Delta Lake! Kyle Weller from Microsoft uncovered how Delta Lake makes time travel possible and why it matters to you. Through presentation, notebooks, and code, he showcased several common applications and how they can improve your modern data engineering pipelines. Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark(TM). It provides snapshot isolation for concurrent read/writes. Enables efficient upserts, deletes, and immediate rollback capabilities. It allows background file optimization through compaction and z-order partitioning achieving up to 100x performance improvements. In this presentation, learn what challenges Delta Lake solves, how Delta Lake works under the hood, and applications of the new Delta Time Travel capability.Get Started with Azure DatabricksThe fun doesn’t stop there! Keep learning more: Webinars Check out our on-demand webinar, From Data to AI with Microsoft Azure Databricks, where you will see how to accelerate your data and AI journey end-to-end with Azure Databricks and our natively integrated data services on Azure. Then see how to accelerate and manage your end-to-end machine learning lifecycle with Azure Databricks—using MLflow and Azure Machine Learning to build, share, deploy, and manage machine learning applications.Try Azure Databricks Get started with Azure Databricks. Sign up for an Azure free account to get instant access. Continue your learning by using Azure Databricks directly.Talk to an expertContact us get answers to questions you might have as you start your first project or to learn more about available training.Follow us on Twitter, LinkedIn, and Facebook for more Azure Databricks news, customer highlights, and new feature announcements.Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/blog/2021/12/17/enabling-computer-vision-applications-with-the-data-lakehouse.html	How to Enable Computer Vision on a Lakehouse, Part 1 - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorEnabling Computer Vision Applications With the Data Lakehouseby Paulo Borges, Bala Amavasai and Bryan SmithDecember 17, 2021 in Engineering BlogShare this postThe potential for computer vision applications to transform retail and manufacturing operations, as explored in the blog Tackle Unseen Quality, Operations and Safety Challenges with Lakehouse enabled Computer Vision, can not be overstated. That said, numerous technical challenges prevent organizations from realizing this potential. In this first introductory installment of our multi-part technical series on the development and implementation of computer vision applications, we dig deeper into these challenges and explore the foundational patterns employed for data ingestion, model training and model deployment.The unique nature of image data means we need to carefully consider how we manage these information assets, and the integration of trained models with frontline applications means we need to consider some non-traditional deployment paths. There is no one-size-fits-all solution to every computer vision challenge, but many techniques and technologies have been developed by companies who've pioneered the use of computer vision systems to solve real-world business problems. By leveraging these, as explored in this post, we can move more rapidly from demonstration to operationalization.Data ingestionThe first step in the development of most computer vision applications (after design and planning) is the accumulation of image data. Image files are captured by camera-enabled devices and transmitted to a central storage repository, where they are prepared for use in model training exercises.It's important to note that many of the popular formats, such as PNG and JPEG, support embedded metadata. Basic metadata, such as image height and width, supports the conversion of pixel values into two-dimensional representations. Additional metadata, such as Exchange Information File Format (Exif) metadata, may be embedded as well to provide additional details about the camera, its configuration, and potentially its location (assuming the device is equipped with GPS sensors).When building an image library, metadata as well as image statistics, useful to data scientists as they sift through the thousands or even millions of images typically accumulating around computer vision applications, are processed as they land in Lakehouse storage. Leveraging common open-source libraries such as Pillow, both metadata and statistics can be extracted and persisted to queryable tables in a Lakehouse environment for easier access. The binary data comprising the image may also be persisted to these tables along with path information for the original file in the storage environment.Model trainingThe size of the individual image files combined with the large number of them needed to train a robust model means that we need to carefully consider how they will be handled during model training. Techniques commonly used in data science exercises such as collecting model inputs to a pandas dataframe will not often work at an enterprise scale due to memory limitations on individual computers. Spark™ dataframes, which distribute the data volumes over multiple computer nodes configured as a computing cluster, are not accessible by most computer vision libraries so another solution to this problem is needed. To overcome this first model training challenge, Petastorm, a data caching technology built specifically for the large-scale training of advanced deep learning model types, can be used. Petastorm allows retrieval of large volumes of data from the Lakehouse and places it in a temporary, storage-based cache. Models leveraging Tensorflow and PyTorch, the two most popular libraries for deep neural network development and commonly employed in computer vision applications, can read small subsets of data in batches from the cache as they iterate over the larger Petastorm dataset.With data volumes manageable, the next challenge is the acceleration of the model training itself. Machine learning models learn through iteration. This means that training will consist of a series of repeated passes over the input dataset. With each pass, the model learns optimized weights for various features that lead to better prediction accuracy.The model's learning algorithm is governed by a set of parameters referred to as hyperparameters. The values of these hyperparameters are often difficult to set based on domain knowledge alone, and so the typical pattern for discovering an optimal hyperparameter configuration is to train multiple models to determine which performs best. This process, referred to as hyperparameter tuning, implies iterations on top of iterations.The trick to working through so many iterations in a timely manner is to distribute the hyperparameter tuning runs across the cluster's compute nodes so that they may be performed in a parallel manner. Leveraging Hyperopt, these runs can be commissioned in waves, between which the Hyperopt software can evaluate which hyperparameter values lead to which outcomes and then intelligently set the hyperparameter values for the next wave. After repeated waves, the software converges on an optimal set of hyperparameter values much faster than if an exhaustive evaluation of values were to have been performed.Once the optimal hyperparameter values have been determined, Horovod can be used to distribute the training of a final model across the cluster. Horovod coordinates the independent training of models on each of the cluster's compute nodes using non-overlapping subsets of the input training data. Weights learned from these parallel runs are consolidated with each pass over the full input set, and models are rebalanced based on their collective learning. The end result is an optimized model, trained using the collective computational power of the cluster.Model deploymentWith computer vision models, the goal is often to bring model predictions into a space where a human operator would typically perform a visual inspection. While centralized scoring of images in the back office may make sense in some scenarios, more typically, a local (edge) device will be handed responsibility for capturing an image and calling the trained model to generate scored output in real time. Depending on the complexity of the model, the capacity of the local device and the tolerance for latency and/or network disruptions, edge deployments typically take one of two forms.With a microservices deployment, a model is presented as a network-accessible service. This service may be hosted in a centralized location or across multiple locations more closely aligned with some number of the edge devices. An application running on the device is then configured to send images to the service to receive the required scores in return. This approach has the advantage of providing the application developer with greater flexibility for model hosting and access to far more resources for the service than are typically available on an edge device. It has the disadvantage of requiring additional infrastructure, and there is some risk of network latency and/or disruption affecting the application.With an edge deployment, a previously trained model is sent directly to the local device. This eliminates concerns over networking once the model has been delivered, but limited hardware resources on the device can impose constraints. In addition, many edge devices make use of processors that are significantly different from the systems on which the models are trained. This can create software compatibility challenges, which may need to be carefully explored before committing resources to such a deployment.In either scenario, we can leverage MLflow, a model management repository, to assist us with the packaging and delivery of the model.Bringing it all together with DatabricksTo demonstrate how these different challenges may be addressed, we have developed a series of notebooks leveraging data captured from a PiCamera-equipped Raspberry Pi device. Images taken by this device have been transmitted to a cloud storage environment so that these image ingestion, model training and deployment patterns can be demonstrated using the Databricks ML Runtime, which comes preconfigured with all the capabilities described above. To see the details behind this demonstration, please refer to the following notebooks:Get the notebookTry Databricks for freeGet StartedRelated postsEnabling Computer Vision Applications With the Data LakehouseDecember 17, 2021 by Paulo Borges, Bala Amavasai and Bryan Smith in Engineering Blog The potential for computer vision applications to transform retail and manufacturing operations, as explored in the blog Tackle Unseen Quality, Operations and Safety... See all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/kr/company/partners/cloud-partners	Databricks 클라우드 서비스 제공업체 파트너 \| DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센터웨비나 5월 18일 / 오전 8시(태평양 표준시) 안녕, 데이터 웨어하우스. 안녕하세요, 레이크하우스입니다. 데이터 레이크하우스가 최신 데이터 스택에 어떻게 부합하는지 이해하려면 참석하십시오. 지금 등록하세요솔루션산업별 솔루션금융 서비스의료 서비스 및 생명 공학제조커뮤니케이션, 미디어 및 엔터테인먼트공공 부문리테일모든 산업 보기사용 사례별 솔루션솔루션 액셀러레이터프로페셔널 서비스디지털 네이티브 비즈니스데이터 플랫폼 마이그레이션5월 9일 \| 오전 8시(태평양 표준시) 제조업을 위한 레이크하우스 살펴보기 코닝이 수동 검사를 최소화하고 운송 비용을 절감하며 고객 만족도를 높이는 중요한 결정을 내리는 방법을 들어보십시오.지금 등록하세요학습관련 문서교육 및 인증데모리소스온라인 커뮤니티University Alliance이벤트Data + AI Summit블로그LabsBeacons2023년 6월 26일~29일 직접 참석하거나 키노트 라이브스트림을 시청하세요.지금 등록하기고객파트너클라우드 파트너AWSAzureGoogle CloudPartner Connect기술 및 데이터 파트너기술 파트너 프로그램데이터 파트너 프로그램Built on Databricks Partner Program컨설팅 & SI 파트너C&SI 파트너 프로그램파트너 솔루션클릭 몇 번만으로 검증된 파트너 솔루션과 연결됩니다.자세히회사Databricks 채용Databricks 팀이사회회사 블로그보도 자료Databricks 벤처수상 실적문의처Gartner가 Databricks를 2년 연속 리더로 선정한 이유 알아보기보고서 받기Databricks 이용해 보기데모 보기문의처로그인JUNE 26-29REGISTER NOWDatabricks클라우드 파트너Databricks 레이크하우스는 모든 주요 퍼블릭 클라우드에서 실행되며, 클라우드 공급업체가 기본적으로 제공하는 보안, 컴퓨팅, 스토리지, 분석, AI 서비스와 긴밀히 통합됩니다. 이는 어디서나 어떤 방식으로든 원하는 클라우드 제공업체를 활용하기 위한 민첩성을 제공합니다.Azure Databricks는 Databricks와 Microsoft가 공동으로 개발한 자체 서비스입니다. Azure Portal에서 클릭 한 번으로 시작하면, Azure 보안 및 데이터 서비스와 기본적으로 통합됩니다.자세히AWS 기반 Databricks를 사용하면 데이터 웨어하우스와 데이터 레이크의 장점을 결합한 간단한 개방형 레이크하우스 플랫폼에 모든 데이터를 저장하여 관리하고, 모든 분석 및 AI 워크로드를 통합할 수 있습니다.자세히Google Cloud의 Databricks는 Google Cloud Storage, BigQuery 및 Google Cloud AI 플랫폼과 긴밀한 통합으로 오픈 클라우드에 개방형 레이크하우스 플랫폼을 제공하여 데이터 엔지니어링, 데이터 사이언스, 분석을 통합합니다.자세히클라우드 리전●Azure ●AWS ●Google ●Alibaba제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티솔루션산업 기준프로페셔널 서비스솔루션산업 기준프로페셔널 서비스회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처Databricks 채용 확인하기WorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark 및 Spark 로고는 Apache Software Foundation의 상표입니다.개인 정보 보호 고지\|이용약관\|귀하의 개인 정보 선택\|귀하의 캘리포니아 프라이버시 권리
https://www.databricks.com/fr/company/partners/cloud-partners	Partenaire fournisseur de services cloud Databricks \| DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai \| 8h PT Découvrez le Lakehouse pour la fabrication Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023 Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWPartenaires cloud DatabricksLakehouse de Databricks fonctionne sur tous les principaux clouds publics, en étant étroitement intégré aux services de sécurité, de calcul, de stockage, d'analytique et d'IA proposés en mode natif par les fournisseurs de cloud. Vous disposez ainsi de la souplesse nécessaire pour tirer parti du fournisseur de cloud de votre choix, quand et comme vous le souhaitez.Azure Databricks est un service de première main développé conjointement par Databricks et Microsoft. Commencez par un simple clic dans le portail Azure et intégrez en mode natif les data services et services de sécurité Azure.En savoir plusDatabricks sur AWS vous permet de stocker et de gérer toutes vos données S3 sur une plateforme lakehouse simple et ouverte qui combine le meilleur des data warehouses et des data lakes pour unifier toutes vos charges de travail d'analytique et d'IA.En savoir plusDatabricks sur Google Cloud apporte la plateforme lakehouse ouverte au cloud ouvert pour unifier le data engineering, la data science et l'analytique, avec une intégration étroite à Google Cloud Storage, BigQuery et à la plateforme d'IA Google Cloud.En savoir plusRégions cloud●Azure ●AWS ●Google ●AlibabaProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterDécouvrez les offres d'emploi chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité\|Conditions d'utilisation\|Vos choix de confidentialité\|Vos droits de confidentialité en Californie
https://www.databricks.com/company/careers/open-positions?department=marketing	Current job openings at Databricks \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/legal/aup	Acceptable Use Policy \| DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesAcceptable Use PolicyAcceptable Use Policy for the paid (including trial) version of DatabricksAcceptable Use Policy for Databricks Community EditionProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/p/ebook/big-book-of-machine-learning-use-cases	The Big Book of Machine Learning Use Cases \| DatabrickseBookThe Big Book of Machine Learning Use Cases – 2nd EditionYour complete how-to guide to putting machine learning to work — plus use cases, code samples and notebooksThe world of machine learning is evolving so quickly that it’s challenging to find real-life use cases that are relevant to your day-to-day work.That’s why we’ve created this comprehensive guide you can start using right away. Get everything you need — use cases, code samples and notebooks — so you can start putting the Databricks Lakehouse Platform to work today.Plus, you’ll get case studies from leading companies like Comcast, Regeneron and Nationwide.Learn how to:Improve on-shelf availability with out of stock modelingMake real-time decisions in professional sports using quantitative modelingUse dynamic time warping and MLflow to detect sales trends seriesPerform multivariate time series forecasting with recurrent neural networksAccess new product capabilities with demosDetect financial fraud at scale with decision trees and MLflow on DatabricksDownload your copyProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/dataaisummit/speaker/yeshwanth-vijayakumar	Yeshwanth Vijayakumar - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYeshwanth VijayakumarSr Engineering Manager/Architect at AdobeBack to speakersYeshwanth Vijayakumar is a Sr Engineering Manager/Architect on the Unified Profile Team in the Adobe Experience Platform; it’s a PB scale store with a strong focus on millisecond latencies and analytical abilities and easily one of Adobe’s most challenging SaaS projects in terms of scale. He is actively designing/implementing the Interactive segmentation capabilities which helps us segment over two million records per second using Apache Spark. He looks for opportunities to build new features using interesting data Structures and Machine Learning approaches. In a previous life, he was a ML Engineer on the Yelp Ads team building models for Snippet Optimizations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/scott-castle	Scott Castle - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott CastleChief Strategy Officer at SisenseBack to speakersScott Castle is Chief Strategy Officer for Sisense, leading go-to-market, cloud, messaging and business strategy. He brings more than 25 years of experience in software development and product management at leading technology companies including Adobe, Periscope Data, Electric Cloud (acquired by Cloudbees), and FileNet (acquired by IBM).Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
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https://www.databricks.com/blog/2020/06/29/celebrating-pride-month-at-databricks.html	LGBTQ Pride Month at Databricks - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorCelebrating Pride Month at Databricksby Jess Chace and Stacy KerkelaJune 29, 2020 in Company BlogShare this postWith Pride month coming to an end, Databricks’ newest Employee Resource Group, Queeries Network, is looking back at how we celebrated. The mission of this group is to create opportunities to come together to discuss topics important to the LGBTQ+ community, network and build community. To celebrate Pride Month, our Queeries Network Employee Resource Group hosted virtual pride socials, participated in virtual pride parades across the globe, and had dialogues around the history of Pride and the intersections with current events impacting the Black community. When we look back at how Pride started, from the Stonewall uprising to what is now an international celebration of the LGBTQ+ community and their contributions to the world, there has been a lot of progress in the fight for gay rights and equality, but there is also more we can do. As we continue this reflection, we’ve asked a few Bricksters, who have made amazing contributions to Databricks, for their thoughts on how we can all create a more inclusive workspace that encourages everyone to bring their authentic self to work. Read more below. How can we create an environment that encourages everyone to be their authentic self and do their best work? One of our core values at Databricks is to be customer obsessed, which at first glance, can sound like a narrow and hyperfocused attention to a singular goal. In practice, what I think it actually means is to be genuinely curious about our customers — to struggle along with them in their challenges and to celebrate in their victories. I think the same applies to how we treat each other. Taking the time to be genuinely curious about someone’s lived experience is hard because it requires a willingness to not have all the answers. But when we spend time and energy investing in and learning from each other, that’s when, in my experience, real success is realized. — Jess Chace (she/her), Customer Success Engineer (New York) It’s critical to show everyone in the company, particularly the newer members who might have less confidence, that there are many ways to be, to find personal success, and to develop as an individual. Offices are usually pretty homogeneous. We have to raise up the less obvious people in our midst, to showcase the realities and the successes of people of all colours, creeds, kinds, sexual and gender identities. A lot of people I speak to who don’t fit naturally into the white, male, heteronormative milieu will talk about the first time they met someone who was different, but successful in their own way. Someone they wanted to emulate. That’s powerful — to show that there are many paths, all of them perfectly valid. It creates new leaders, and it creates the foundation for the next generation of difference and variety, of authenticity. — Rob Anderson (he/him), Director of Field Engineering (London) I start by focusing on the details of things like inclusive language, especially within an interview setting. Those early interactions are some of the most stressful moments in anyone’s life, we shouldn’t make them more difficult. I’ve been particularly thoughtful about my choice of words while answering questions during the hiring process about the challenges of relocating with a partner or family or when discussing parental benefits. I’ve had some people mention, after joining Databricks, how significant these small choices were to them as a signal of our values. — Stacy Kerkela (she/her), Director of Engineering (Amsterdam) Creating an environment at work for Bricksters to be their most authentic selves is critical to building an inclusive and collaborative culture. Being “authentic” might seem like a simple concept; however, many individuals from marginalized backgrounds are oftentimes code switching or shrinking pieces of themselves to fit into the majority culture. One of our company values that is most salient to me is: Teamwork makes the dream work. To promote authenticity within the workplace, we should encourage our team members to build genuine connections with one another, amplify our strengths and, most importantly, actively listen and promote empathy — even during challenging or unpredictable times. As a queer Black femme, who holds many other marginalized identities, oftentimes I am navigating various environments and interacting with diverse audiences and stakeholders. I am always looking to build strong partnerships and bring my authentic self to interactions with candidates, colleagues and executives. Promoting an inclusive environment where trust and vulnerability are at the core is extremely important for me to do my best work and feel supported in doing so. — Kaamil Al-Hassan (she/her), Talent Acquisition (San Francisco)How does focusing on nurturing this inclusive environment help us have a greater impact at Databricks and in our communities? Another one of our core values at Databricks is to let the data decide, and it’s no secret that having a more diverse and inclusive work environment correlates with many positive business outcomes like higher innovation revenues, greater market share and greater returns to shareholders. The true value of promoting diversity and inclusion, however, is so much more than monetary gains. When our work reflects the voices and minds of our actual communities, it is better positioned to serve us all. — Jess Chace (she/her), Customer Success Engineer (New York) Databricks is a member of the technology community, where there is a great opportunity to continue to increase the representation of women, ethnic minorities, and people of various ages as well as sexual and gender identities. I believe that we will make the biggest impact by investing in how we hire diverse teams and support the incredible talent from these under-represented groups. There is a lot we can do to have a big impact on our companies and our communities at large. — Rob Anderson (he/him), Director of Field Engineering (London) At Databricks, I build teams that I would want to belong to. That means having the safety to be my authentic self and providing that same comfort zone to everyone around me. This year as entire companies have moved to work-from-home models, there’s a lot of visibility into all of our home lives that makes it impossible for me to live less openly. Engaging with teammates via video calls at home can make it difficult to create separate home and work identities, especially for members of the LGBTQ+ community. It is important that we focus on creating an inclusive culture so everyone can feel comfortable and confident being their authentic selves and doing their best work without the stress or anxiety of wondering if they will be accepted. The impact of that care we show for one another and our dedication to inclusion is huge for our entire community. — Stacy Kerkela (she/her), Director of Engineering (Amsterdam) Being queer means that every day I am ”coming out.” When I go to the grocery store with my partner, when someone inquires about my ”boyfriend,” or when I attend our company holiday party and my partner is slaying in her tuxedo but is also wearing makeup. Coming out is not a singular moment. Creating an inclusive culture includes feeling supported by my colleagues and exemplifying my authentic queer self. Our impact will be even greater when we invite members of the LGBTQ+ community to join our global teams through investing in targeted outreach events. Building an inclusive culture means exploring the possibility of gender-neutral bathrooms and encouraging pronoun usage in everyday conversations. I am excited for us to celebrate Pride and for the resilience of this particular community that is still fighting every day for equal rights and visibility. I look forward to getting more involved in the newly formed LGBTQ+ ERG and exploring ways to create inclusivity and highlight the queer experience here at Databricks. — Kaamil Al-Hassan (she/her), Talent Acquisition (San Francisco)It was great to launch our Queeries Network Employee Resource Group and celebrate Pride Month together. To learn more about how you can join us, check out the Careers page. Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. 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https://www.databricks.com/fr/learn/labs	Databricks Labs Projects \| DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks LabsDatabricks Labs are projects created by the field team to help customers get their use cases into production faster!DBXThis tool simplifies jobs launch and deployment process across multiple environments. It also helps to package your project and deliver it to your Databricks environment in a versioned fashion. Designed in a CLI-first manner, it is built to be actively used both inside CI/CD pipelines and as a part of local tooling for fast prototyping.GitHub Sources →Documentation →Blog →TempoThe purpose of this project is to provide an API for manipulating time series on top of Apache Spark™. Functionality includes featurization using lagged time values, rolling statistics (mean, avg, sum, count, etc.), AS OF joins, and downsampling and interpolation. This has been tested on TB-scale of historical data.GitHub Sources →Documentation →Webinar →MosaicMosaic is a tool that simplifies the implementation of scalable geospatial data pipelines by binding together common open source geospatial libraries and Apache Spark™️. Mosaic also provides a set of examples and best practices for common geospatial use cases. It provides APIs for ST_ expressions and GRID_ expressions, supporting grid index systems such as H3 and British National Grid.GitHub Sources →Documentation →Blog →Other ProjectsOverwatchAnalyze all of your jobs and clusters across all of your workspaces to quickly identify where you can make the biggest adjustments for performance gains and cost savings.Learn moreSplunk IntegrationAdd-on for Splunk, an app that allows Splunk Enterprise and Splunk Cloud users to run queries and execute actions, such as running notebooks and jobs, in Databricks.Github Sources →Learn more →SmolderSmolder provides an Apache Spark™ SQL data source for loading EHR data from HL7v2 message formats. Additionally, Smolder provides helper functions that can be used on a Spark SQL DataFrame to parse HL7 message text, and to extract segments, fields, and subfields from a message.Github Sources →Learn more →GeoscanApache Spark ML Estimator for density-based spatial clustering based on Hexagonal Hierarchical Spatial Indices.Github Sources →Learn more →MigrateTool to help customers migrate artifacts between Databricks workspaces. This allows customers to export configurations and code artifacts as a backup or as part of a migration between a different workspace.Github SourcesLearn more: AWS \| AzureData GeneratorGenerate relevant data quickly for your projects. The Databricks data generator can be used to generate large simulated/synthetic data sets for test, POCs, and other usesGithub Sources →Learn more →DeltaOMSCentralized Delta transaction log collection for metadata and operational metrics analysis on your Lakehouse.Github Sources →Learn more →DLT-METAThis framework makes it easy to ingest data using Delta Live Tables and metadata. With DLT-META, a single data engineer can easily manage thousands of tables. Several Databricks customers have DLT-META in production to process 1000+ tables.Github Sources →Learn more →Please note that all projects in the https://github.com/databrickslabs account are provided for your exploration only, and are not formally supported by Databricks with service level agreements (SLAs). They are provided AS IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects. Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/blog/2021/03/30/creating-growth-and-advancement-opportunities-introducing-the-women-in-tech-mentorship-program.html	Databricks’ Women in Tech Mentorship Program - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorCreating Growth and Advancement Opportunities: Introducing the Women in Tech Mentorship Programby Alexandra Bellogini, Christina Patel and Samantha MenotMarch 30, 2021 in Company BlogShare this postAt Databricks, we recognize the importance of offering professional growth and advancement opportunities for all communities and are committed to fostering a work environment where every employee can contribute the best work of their careers. This week, we’re wrapping up our celebration of Women’s History Month. In alignment with our commitment to employee growth, we wanted to highlight our newly launched global Women in Tech Mentorship pilot program. We strongly believe that mentorship is a key piece to driving more career advancement, especially for women in technology and STEM fields such as computer science. With this growth mindset, as well as direct feedback from our employees, we're proud to launch this program. The objective of the mentorship program is to support the professional development of women across the company while building a community and support network within all functions and geographies. The initiative is a 6-month long program consisting of two main components: monthly group sessions with the entire cohort and monthly individual mentoring sessions with an assigned role model. To assess the value of the program, participants were asked to complete a pre-program survey to clarify their current understanding of the topics mentioned above. Over the course of the program, participants will be asked to complete a monthly survey and final questionnaire once the program has come to a close. Learn more about our employee perspectives on mentorship in this conversation between a current program pairing: mentee Samantha Menot (Senior Customer Growth Program Manager) and mentor Alexandra Bellogini (Manager, Technical Solutions): What is the most valuable aspect of participating in a mentorship program at Databricks? Sam: For me, I think it’s being able to build relationships with people who we wouldn’t normally connect with back in the office. It gives us great networking opportunities. That’s definitely the number one reason why I decided to join the mentorship program. Alex: I would agree with you Sam. The most valuable part of this program is having the opportunity to connect with others outside of our own team. I also love having the opportunity to mentor and being able to share my own experiences with you and watch you grow in your career. Out of the topics we are covering during the program, such as personal branding and negotiating, which one are you most passionate about and why? Sam: I would definitely like to learn more about negotiating, as I have only really thought about negotiating a few times in my career. I am still learning how to go into a negotiation, what makes a strong negotiator and how to present and position yourself in a negotiation. Alex: Negotiating is a big area I would like to learn more about also, but personal branding is an important one for me. It’s great to have the opportunity to really stop and think about who I am now and what I want to be, as personal branding is something that shifts throughout your career. What do you hope to learn from each other during this experience?Sam: Based on the first couple of sessions that we’ve had, I’m looking forward to learning more about personal branding. I’m trying to figure out what my brand is right now and what I would like it to be. It’s been helpful being able to have an honest conversation with [Alex], and to hear about the experiences you have had within your own career. Alex: One of the biggest parts and for me as a mentor is to learn from you and the experiences you have had. I think it’s important to hear about how you have dealt with certain situations in your career and to compare them to my own similar situations in order to understand what could have been done better. I’m also interested in hearing about your role, how you interact with others and the challenges you face, and what I can learn from that. Our goal is for the program to serve as a valuable tool in providing guidance, advocacy and navigation through important career milestones. As the Women in Tech mentorship program continues to grow, we look forward to hearing about the continued positive impact it will have for both mentors and mentees across the company. Interested in joining Databricks?Visit our careers page to explore our global opportunities and to learn more about how you can join our Databricks community.Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/jp/product/delta-lake-on-databricks	Databricks on Delta Lake - 今すぐデモをご予約ください。Skip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT さようなら、データウェアハウス。こんにちは、レイクハウス。データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 \|午前8時(太平洋標準時) 製造業のためのレイクハウスを発見するコーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOWDelta Lakeデータスワンプからの脱却とデータ加工の柔軟性をもたらす、次世代型データレイク／データウェアハウス無料トライアルデモ動画を見るDelta Lake とはDelta Lake（デルタレイク）は、AWS S3、Azure Data Lake Storage、HDFS などの既存のデータレイクファイルストレージ上に構築されるオープンソースのストレージレイヤーです。データレイクの信頼性、セキュリティ、性能を高め、ストリーミング／バッチ処理の両方に柔軟に対応します。構造化、半構造化、非構造化データを単一システムに集約してデータサイロを解消し、コスト効率およびスケーラビリティの高いレイクハウスを実現します。データスワンプからの脱却リアルタイムストリームを含む、すべてのデータの信頼できる単一真実情報源を提供し、データチームが常に最新のデータで作業できるようにします。ACIDトランザクションとスキーマエンフォースメントのサポートにより、Delta Lakeは、従来のデータレイクに欠けていた信頼性を提供します。信頼性の高い、最新のデータを組織全体で活用し、分析をはじめとするデータプロジェクトをデータレイク上で直接実行できるようになります。結果として、データドリブンな意思決定が最大 50 倍高速化します。オープンでセキュアなデータ共有Delta Sharing は、セキュアなデータ共有のための新しいオープンプロトコルです。データの場所を問わず、組織内外でのデータ共有を容易にします。Unity Catalog とのネイティブな統合により、組織間の共有データを一元管理、監視できます。データアセットをベンダーやパートナーとセキュアに共有して連携を強化すると同時に、セキュリティおよびコンプライアンスの要件を満たします。また、主要なツールやプラットフォームとの統合により、任意のツールを使用した共有データの視覚化、クエリ、エンリッチメント、ガバナンスが可能です。超高速性能Apache Spark™ を基盤とする Delta Lake は、大規模なスケーリングと高速性を実現します。性能を左右するインデックス機能などの最適化により、ETL ワークロードが最大 48 倍高速化したことが実証されています。オープン、アジャイルDelta Lake のデータはオープンな Apache Parquet 形式で保存されるため、あらゆる互換リーダーで読み取ることができます。API はオープンで、Apache Spark と互換性があり、データパイプラインの変更は最小限ですみます。Databricks で Delta Lake を利用することで、オープンソースの広範なエコシステムへのアクセスが可能になり、独自形式によるデータのロックインを回避できます。データエンジニアリングの自動化と高信頼性Delta Live Tables が Delta Lake のデータを最新かつ高品質に保つデータパイプラインの構築・管理を容易にし、データエンジニアリングをシンプルにします。また、宣言型パイプラインの開発、高信頼性データ、クラウドスケールの本稼働環境がレイクハウス基盤の構築を可能にし、データエンジニアリングによる ETL の開発・管理をシンプルにします。大規模運用のためのセキュリティとガバナンスDelta Lake は、詳細なアクセス制御によりデータガバナンスを確実にしてリスクを軽減します。これは通常のデータレイクでは不可能です。データレイクのデータを迅速かつ正確に更新し、GDPR をはじめとする規制へのコンプライアンス、監査ログによる高度なデータガバナンスの維持を可能にします。これらのケイパビリティは、レイクハウス初のマルチクラウドデータカタログである Unity Catalog の一部としてDatabricks にネイティブに統合され、拡張されています。ユースケースリアルタイムデータによる BIビジネスインテリジェンス（BI）のワークロードをデータレイク上で直接実行することで、新鮮なリアルタイムデータの素早いクエリを可能にし、データドリブンな意思決定を加速させます。Delta Lake は、データウェアハウスの性能とデータレイクの経済性を同時に実現するマルチクラウドのレイクハウスアーキテクチャの運用を可能にします。SQL ワークロードの実行においては、従来のクラウド型データウェアハウスと比較して最大 6 倍の価格性能を発揮します。詳しく見るバッチ／ストリーミングの両方に対応バッチ／ストリーミング両方の入力を単一のシンプルなアーキテクチャで処理し、冗長なシステムや運用上の課題を回避します。Delta Lake のテーブルは、バッチテーブルでもあり、ストリーミングソースとシンクでもあります。ストリーミングデータの取り込み、バッチ履歴バックフィル、対話型クエリは全てすぐに動作し、Spark の構造化ストリーミングと直接統合されます。規制への対応Delta Lake は、不正なデータの取り込み、コンプライアンスのためのデータ削除、変更データキャプチャのためのデータの変更といった課題を解決します。データレイクでの ACID トランザクションがサポートされているため、全操作を成功させるか、または、再実行に備えて全操作を完全に中断させます。データパイプラインを新たに作成する必要はありません。さらに、Delta Lake によって、全トランザクションの履歴がデータレイクに記録されます。過去のバージョンのデータに容易にアクセス可能にすることで、GDPR／CCPA などのコンプライアンス要件を満たします。データインジェストのネットワークネイティブのコネクタが、あらゆるアプリケーション、データベース、ファイルストレージからのデータを迅速・容易に Delta Lake に取り込みます。導入事例「Databricks の導入によって市場投入までの時間を短縮できました。分析や運用管理が効率化し、医療部門の新たなニーズに対応できるようになっています。」ヘルスダイレクト・オーストラリア社チーフアーキテクトピーター・ジェームズ氏詳しく見る「Databricks と Delta Lake を活用することで、組織内での大規模なデータ共有が可能になっています。さらに、本運用ワークロードの実行に伴うコストが 60% 低減し、数百万ドルのコスト削減を達成しました。」 YipitＤata 社 CTO スティーブ・ピュレック氏詳しく見る「Delta Lake は、データパイプラインの運用をシンプルにする ACID 特性によって、パイプラインの信頼性とデータの一貫性を向上させます。また、キャッシングやインデックス自動作成などの機能が、効率的なデータアクセスを可能にします。」コロンビアスポーツウェア社シニアエンタープライズデータマネージャーララ・マイナー氏詳しく見る「Delta Lake でデータパイプラインの管理がシンプルになりました。運用コストも低減し、ダウンストリームの分析とデータサイエンスによる気づきの発見がスピードアップしています。」 Viacom18 社デジタル変革・技術部門アシスタント VP パリヤット・デイ氏詳しく見る関連リソース関連リソース一覧データエンジニアリングにおける Databricks 活用のメリットとは？eBook や動画などの関連リソースが見つかります。詳しく見るeBookデータ工学ユースケース大全データ、分析、AI ガバナンスデータマネジメント入門データレイクハウスの構築（データウェアハウス提唱者 Bill Inmon 著）テックトークDelta Lake入門 - Tech TalkシリーズWeb セミナー良いこと悪いこと醜いことデルタレイクのあるレイクハウスを深堀りする無料お試し・その他ご相談を承りますDatabricks 無料トライアルDelta Lake 関連のドキュメント製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/kr/solutions/industries/federal-government	연방 기관을 위한 데이터 분석 및 AI \| DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센터웨비나 5월 18일 / 오전 8시(태평양 표준시) 안녕, 데이터 웨어하우스. 안녕하세요, 레이크하우스입니다. 데이터 레이크하우스가 최신 데이터 스택에 어떻게 부합하는지 이해하려면 참석하십시오. 지금 등록하세요솔루션산업별 솔루션금융 서비스의료 서비스 및 생명 공학제조커뮤니케이션, 미디어 및 엔터테인먼트공공 부문리테일모든 산업 보기사용 사례별 솔루션솔루션 액셀러레이터프로페셔널 서비스디지털 네이티브 비즈니스데이터 플랫폼 마이그레이션5월 9일 \| 오전 8시(태평양 표준시) 제조업을 위한 레이크하우스 살펴보기 코닝이 수동 검사를 최소화하고 운송 비용을 절감하며 고객 만족도를 높이는 중요한 결정을 내리는 방법을 들어보십시오.지금 등록하세요학습관련 문서교육 및 인증데모리소스온라인 커뮤니티University Alliance이벤트Data + AI Summit블로그LabsBeacons2023년 6월 26일~29일 직접 참석하거나 키노트 라이브스트림을 시청하세요.지금 등록하기고객파트너클라우드 파트너AWSAzureGoogle CloudPartner Connect기술 및 데이터 파트너기술 파트너 프로그램데이터 파트너 프로그램Built on Databricks Partner Program컨설팅 & SI 파트너C&SI 파트너 프로그램파트너 솔루션클릭 몇 번만으로 검증된 파트너 솔루션과 연결됩니다.자세히회사Databricks 채용Databricks 팀이사회회사 블로그보도 자료Databricks 벤처수상 실적문의처Gartner가 Databricks를 2년 연속 리더로 선정한 이유 알아보기보고서 받기Databricks 이용해 보기데모 보기문의처로그인JUNE 26-29REGISTER NOW연방 기관을 위한 데이터 분석 및 AI데이터 및 머신 러닝으로 더 나은 공공 서비스를 제공하기 위한 혁신 추진연방 데이터 전략에서 AI 행정 명령에 이르기까지 미국 연방 정부가 데이터 분석과 웨어하우징 기능을 현대화하는 데 집중하고 있다는 점은 명백합니다.Databricks 레이크하우스 플랫폼은 연방 기관이 데이터의 완전한 잠재력을 실형하여 미션 목표를 달성하고 공공 서비스를 개선하도록 지원합니다.연방 기관이 데이터 및 AI를 활용하여 미션 목표를 달성하도록 지원주요 공공 기관에서 신뢰+ 여타 모든 Apache Spark™️ 호환 클라이언트산업 리더들이 어떻게 Databricks를 사용하여 모든 공공 서비스 환경을 개선하는지 알아보세요.최신 블로그 게시물, 웨비나, 사례 연구연방 정부에서 Databricks를 사용해야 하는 이유데이터 분석 현대화130자 기술 스택을 현대화하여 가장 빠른 대규모 DNAQSeq 파이프라인으로 환자 및 의사를 위한 환경을 개선합니다.미션 결과를 효과적, 효율적으로 달성130자 기술 스택을 현대화하여 가장 빠른 대규모 DNAQSeq 파이프라인으로 환자 및 의사를 위한 환경을 개선합니다.시민을 위한 더 나은 환경 구현130자 기술 스택을 현대화하여 가장 빠른 대규모 DNAQSeq 파이프라인으로 환자 및 의사를 위한 환경을 개선합니다.자세히빠르고 간편한 운영 승인(ATO)으로 광범위한 규정 준수Databricks는 지역, 네트워크 및 규정 준수 컨트롤에서 ATO를 통해 미션 목표 지원클라우드C2S SC2S GovCloud 퍼블릭 클라우드 네트워크퍼블릭 NIPR SIPR JWICS 규정 준수 관리FedRAMP FedRAMP-High FISMA IL5 IL6 ICS-503 Databricks가 연방 정부의 혁신을 가속화하는 방법의료 서비스효과적인 분석과 환자 360도 뷰를 통해 공공 의료 서비스 품질과 제공 방식을 개선합니다. 환자 360 공급망 최적화 보험 관리 유전체학 약물 발견 및 전달국방지리, IoT, 보안 감시 데이터에 예측 분석을 적용하여 운영을 개선하고 국가를 보호합니다. 물류 예측적 유지관리 보안 감시 및 정찰 법 집행 및 준비국토 안보실시간 분석과 데이터 중심 의사 결정으로 범죄 활동과 국가적 위협을 발견하여 예방합니다. 세관 및 국경 보호 이민 및 시민권 테러 대책 연방 긴급 지원 관리공공 기관/상거래머신 러닝으로 이상을 미리 탐지하여 위험을 완화하고 사기 활동을 예방합니다. 세금 사기 및 징수 프로세스 및 운영 관리 보조금 관리 고객 360에너지데이터 인사이트로 에너지 관리를 개선하여 에너지 회복성과 지속가능성을 보장합니다. 에너지 인프라 보안 더욱 지능적인 에너지 관리 에너지 탐사 전력망 안정성정보국실시간 인사이트를 정보로 활용하여 시민과 세계의 안전에 영향을 미칠 수 있는 결정을 내립니다. 위협 탐지 사이버 공격 무력화 정보 보안 감시 및 정찰 소셜 미디어 분석리소스고객 사례CMS의 환자 중심 디지털 혁신데이터 거버넌스 모범 사례 — Centers for Medicare and Medicaid Services에서 배운 교훈USCIS 데이터 분석 플랫폼 현대화로 얻은 교훈빅데이터와 AI로 공군 현대화웨비나COVID-19 팬데믹 중 데이터와 AI를 사용하여 병원 운영에 대응공공 부문의 특정 지역 관련 분석과 AI 사용 사례정부를 위한 현대적 데이터 분석 아키텍처빅데이터와 AI로 위협 탐지 개선뉴스Azure Databricks, Microsoft Azure Government(MAG)에서 FedRAMP High Authorization 취득AWS 클라우드의 정부 등급 보안정부 고객에게 통합 분석 제공미션 크리티컬 분석과 AI로 미국 정보국 지원서밋 토크Federal Aviation Administration(FAA)의 시스템 정보 관리(SWIM) 데이터 수집과 분석 자동화대규모 지리 분석: 팬데믹 중 인간의 움직임 패턴 분석시작할 준비가 되셨나요?귀사의 비즈니스 목표를 자세히 알아보고 서비스 팀에서 귀사의 성공을 도울 방법을 함께 알아보고자 합니다.무료 시험판사용해 보기문의제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티솔루션산업 기준프로페셔널 서비스솔루션산업 기준프로페셔널 서비스회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처Databricks 채용 확인하기WorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark 및 Spark 로고는 Apache Software Foundation의 상표입니다.개인 정보 보호 고지\|이용약관\|귀하의 개인 정보 선택\|귀하의 캘리포니아 프라이버시 권리
https://www.databricks.com/explainable-ai	Data Lakehouse Architecture and AI Company - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWThe best data warehouse is a lakehouseUnify all your data, analytics and AI on one platformGet started for freeLearn moreCut costs and speed up innovation on the Lakehouse PlatformLearn moreUnifiedOne platform for your data, consistently governed and available for all your analytics and AIOpenBuilt on open standards and integrated with every cloud to work seamlessly within your modern data stackScalableScale efficiently with every workload from simple data pipelines to massive LLMsData-driven organizations choosing Lakehouse See all customers Lakehouse unifies your data teamsData management and engineeringStreamline your data ingestion and managementWith automated and reliable ETL, open and secure data sharing, and lightning-fast performance, Delta Lake transforms your data lake into the destination for all your structured, semi-structured and unstructured data.Learn more Watch demoData warehousingDerive new insights from the most complete dataWith ready access to the freshest and most complete data and the power of Databricks SQL — up to 12x better price/performance than traditional cloud data warehouses — data analysts and scientists can now quickly derive new insights.Learn more Watch demoData science and machine learningAccelerate ML across the entire lifecycleThe lakehouse forms the foundation of Databricks Machine Learning — a data-native and collaborative solution for the full machine learning lifecycle, from featurization to production. Combined with high-quality, highly performant data pipelines, lakehouse accelerates machine learning and team productivity.Learn more Watch demoData governance and sharingUnify governance and sharing for data, analytics and AIWith Databricks, you gain a common security and governance model for all of your data, analytics and AI assets in the lakehouse on any cloud. You can discover and share data across data platforms, clouds or regions with no replication or lock-in, as well as distribute data products through an open marketplace.Learn more Watch demoThe data warehouse is history. Discover why the lakehouse is the modern architecture for data and AI.Discover LakehouseJoin Generation AILearn about the latest innovations with LLMs like Dolly and other open source Data + AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingRegister nowSee why Gartner named Databricks a Leader for the second consecutive year.Get the reportWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowA must-read for ML engineers and data scientists seeking a better way to do MLOps.Get the eBookReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. 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https://www.databricks.com/fr/company/leadership-team	Équipe de direction \| DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai \| 8h PT Découvrez le Lakehouse pour la fabrication Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023 Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWLeadershipAvec une vision à long terme, notre équipe de direction s'appuie sur des décennies d'expérience pour mettre en place une nouvelle voie pour les données et l'IADécouvrez notre équipeÉquipe de directionFoundersConseil d'administrationAli GhodsiCofondateur et directeur généralAndy KofoidPresident, Global Field OperationsDavid ConteDirecteur financierAmy ReichanadterDirecteur des ressources humainesTrâm PhiSVP, General CounselRon GabriskoChief Revenue OfficerRick SchultzDirecteur marketingHatim ShafiqueDirecteur des opérationsFermín SernaDirecteur de la sécuritéNaveen ZutshiDSIVinod MarurSVP of EngineeringDavid MeyerSVP of ProductsAdam ConwaySVP of ProductsArsalan Tavakoli-ShirajiCofondateur, SVP of Field EngineeringProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterDécouvrez les offres d'emploi chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité\|Conditions d'utilisation\|Vos choix de confidentialité\|Vos droits de confidentialité en Californie
https://www.databricks.com/dataaisummit/speaker/miao-wang/#	Miao Wang - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMiao WangSenior Engineering Manager at AdobeBack to speakersMiao is a Senior Engineering Manager at Adobe, where he works with a great team on platform engineering with Spark and other open-source technologies. He was an active Spark contributor before changing to his manager role. His interests span high-speed networks, data center infrastructure, data processing, and machine learning. Prior to joining Adobe, he worked at A10 Networks, IBM, and Alibaba in various engineering roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/glossary/data-vault	What is a Data Vault?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWData VaultAll>Data VaultTry Databricks for freeGet StartedWhat is a data vault?A data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.Hubs represent core business concepts, links represent relationships between hubs, and satellites store information about hubs and relationships between them.The data vault is a data model that is well-suited to organizations that are adopting the lakehouse paradigm.Data vault modeling: Hubs, links, and satellitesHubs - Each hub represents a core business concept, such as they represent Customer Id/Product Number/Vehicle identification number (VIN). Users will use a business key to get information about a Hub. The business key may have a combination of business concept ID and sequence ID, load date, and other metadata information.Links - Links represent the relationship between Hub entities.Satellites - Satellites fill the gap in answering the missing descriptive information on core business concepts. Satellites store information that belongs to Hub and relationships between them.A few additional things to keep in mind:A satellite cannot have a direct connection to another satellite.A hub or link may have one or more satellites.Data vault benefitsAgileStructured, with flexibility for refactoringExtremely scalable, up to PBs volumesUses patterns that support ETL code generationFamiliar architecture: data layers, ETL, star schemasData vaults are based on agile methodologies and techniques, which means that they can adapt to fast-paced changing business requirements. One of the major advantages of using the Data Vault methodology is that ETL jobs need less refactoring when the model changes.Modeling techniques by lakehouse layerWith these concepts in mind, let's explore how Data Vault fits into our Bronze, Silver and Gold data layers where data goes from a raw to a refined state that is ready for analytics. In this multi-hop architecture, raw data gets stored in a Bronze layer with minimum transformation and data structure as close to the source system. The Data Vault methodology can be applied to the Silver layer where data is transformed into Hubs, links and satellites.In the Gold layer, multiple data marts/data warehouses can be built as per dimensional modeling/Kimball methodology. As discussed earlier, the Gold layer is for reporting and uses more de-normalized and read-optimized data models with fewer joins. Sometimes tables in the Gold Layer can be completely denormalized, typically if the Data Scientists want it that way to feed their algorithms for feature engineering.If a Data Vault model is used in the Silver layer it simplifies and significantly reduces the changes needed to perform ETL into the Data Marts and Data Warehouses, as Hubs make key management (surrogate key / natural keys) easier. Satellites make loading dimensions easier because they have all the attributes, and links make loading fact tables quite straightforward because they have all the relationships.ResourcesData Lakehouse Platform by DatabricksDatabricks SQL product pageDatabricks Blog: Different Data Warehousing Modeling Techniques and How to Implement them on the Databricks Lakehouse PlatformDatabricks Blog: What’s a Data Vault and How to Implement It on the Databricks Lakehouse PlatformBack to GlossaryLearn what’s driving the Lakehouse pattern.REGISTER NOWProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/br/company/partners	Parceiros \| DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernança de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePreçosMarketplaceTecnologia de código abertoCentro de segurança e confiançaWEBINAR Maio 18 / 8 AM PT Adeus, Data Warehouse. Olá, Lakehouse. Participe para entender como um data lakehouse se encaixa em sua pilha de dados moderna. Inscreva-se agoraSoluçõesSoluções por setorServiços financeirosSaúde e ciências da vidaProdução industrialComunicações, mídia e entretenimentoSetor públicoVarejoVer todos os setoresSoluções por caso de usoAceleradores de soluçãoServiços profissionaisNegócios nativos digitaisMigração da plataforma de dados9 de maio \| 8h PT Descubra a Lakehouse para Manufatura Saiba como a Corning está tomando decisões críticas que minimizam as inspeções manuais, reduzem os custos de envio e aumentam a satisfação do cliente.Inscreva-se hojeAprenderDocumentaçãoTreinamento e certificaçãoDemosRecursosComunidade onlineAliança com universidadesEventosData+AI SummitBlogLaboratóriosBeaconsA maior conferência de dados, análises e IA do mundo retorna a São Francisco, de 26 a 29 de junho. ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConexão de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSoluções para parceirosConecte-se com apenas alguns cliques a soluções de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de AdministraçãoBlog da empresaImprensaDatabricks VenturesPrêmios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como líder pelo segundo ano consecutivoObtenha o relatórioExperimente DatabricksAssista às DemosEntre em contatoInício de sessãoJUNE 26-29REGISTER NOWParcerias com DatabricksA Databricks conta com mais de 1200+ parcerias em todo o mundo, fornecendo soluções e serviços de dados, análises e IA para nossos clientes mútuos usando a Databricks Lakehouse Platform. Essas parcerias permitem aproveitar a Databricks para unificar todos os dados e cargas de trabalho de IA e obter insights mais relevantes.“A Databricks gerencia a quantidade de dados enquanto o Tableau acelera a visualização. Essas soluções formam um conjunto perfeito no centro da nossa plataforma, oferecendo aos nossos clientes o desempenho de que precisam para fornecer recursos de veículos autônomos de ponta.”— Patrick McAuliffe, engenheiro líder da InciteParceiros de nuvemA Databricks é executada em AWS, Microsoft Azure, Google Cloud e Alibaba Cloud, com integração profunda com a infraestrutura, os dados e os serviços de IA de cada provedorSaiba maisParcerias de tecnologiaAs parcerias de tecnologia integram suas soluções com a Databricks para fornecer recursos complementar de ETL, ingestão de dados, BI, ML e governançaSaiba maisParcerias de consultoriaAs parcerias de consultoria contam com especialistas que ajudam você a criar, implementar e dimensionar dados, análises e iniciativas de IA com a DatabricksSaiba maisComece uma parceriaNossos parceiros trabalham com a Databricks para desenvolver e fornecer soluções inovadoras para os clientes. Participe do Databricks Partner Program e obtenha acesso a ferramentas, treinamento, aceleradores de soluções e programas de lançamento no mercado.Saiba maisProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Aviso de privacidade\|Termos de Uso\|Suas opções de privacidade\|Seus direitos de privacidade na Califórnia
https://www.databricks.com/p/webinar/202109-amer-ve-healthcare-and-life-sciences-workshop-accelerate-rd-with-r	Resources - DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWResourcesLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/dataaisummit/speaker/paul-mracek/#	Paul Mracek - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul MracekSenior Solutions Architect at DatabricksBack to speakersPaul Mracek has 15 years of Data and AI experience. He joined Databricks in 2021 and has supported Honeywell since 2022.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/antonio-castelo	Antonio Castelo - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAntonio Castelo CollibraBack to speakersAntonio built the first partner integration with Unity Catalog, and has been instrumental in building customer momentum around the partnership with Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/kr/customers?itm_data=hp-promo-customerlogos-seeallcustomers	Databricks 고객 \| DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센터웨비나 5월 18일 / 오전 8시(태평양 표준시) 안녕, 데이터 웨어하우스. 안녕하세요, 레이크하우스입니다. 데이터 레이크하우스가 최신 데이터 스택에 어떻게 부합하는지 이해하려면 참석하십시오. 지금 등록하세요솔루션산업별 솔루션금융 서비스의료 서비스 및 생명 공학제조커뮤니케이션, 미디어 및 엔터테인먼트공공 부문리테일모든 산업 보기사용 사례별 솔루션솔루션 액셀러레이터프로페셔널 서비스디지털 네이티브 비즈니스데이터 플랫폼 마이그레이션5월 9일 \| 오전 8시(태평양 표준시) 제조업을 위한 레이크하우스 살펴보기 코닝이 수동 검사를 최소화하고 운송 비용을 절감하며 고객 만족도를 높이는 중요한 결정을 내리는 방법을 들어보십시오.지금 등록하세요학습관련 문서교육 및 인증데모리소스온라인 커뮤니티University Alliance이벤트Data + AI Summit블로그LabsBeacons2023년 6월 26일~29일 직접 참석하거나 키노트 라이브스트림을 시청하세요.지금 등록하기고객파트너클라우드 파트너AWSAzureGoogle CloudPartner Connect기술 및 데이터 파트너기술 파트너 프로그램데이터 파트너 프로그램Built on Databricks Partner Program컨설팅 & SI 파트너C&SI 파트너 프로그램파트너 솔루션클릭 몇 번만으로 검증된 파트너 솔루션과 연결됩니다.자세히회사Databricks 채용Databricks 팀이사회회사 블로그보도 자료Databricks 벤처수상 실적문의처Gartner가 Databricks를 2년 연속 리더로 선정한 이유 알아보기보고서 받기Databricks 이용해 보기데모 보기문의처로그인JUNE 26-29REGISTER NOWDatabricks 고객다양한 업종의 혁신 기업에서 성공을 위해 Databricks 레이크하우스 플랫폼을 어떻게 활용하고 있는지 알아보기추천 사례 고객 사례 수천만 명의 글로벌게임 사용자를 담은데이터 레이크하우스 데브시스터즈의 ‘쿠키런: 킹덤’은 전 세계적으로 4천만 명 이상의 유저를 확보하고 있습니다. 게임 유저와 데이터가 계속 증가하면서 성능 이슈가 발생했고 복잡하고 관리가 어려운데 유지 관리 비용도 많이 드는 자체 구축 플랫폼보다 더 높은 수준의 데이터 분석 솔루션이 필요했습니다. 더 읽어보기 고객 사례 인사이트 기반 대시보드 활용을 통한 고객 확보증대 Bagelcode는 전 세계 200여 개국에 5,000만 명 이상의 게임 이용자를 보유한 글로벌 게임 업체입니다. 자세히 읽기 고객 사례 팬덤 데이터로 팬 경험 향상 Weverse Company는 지난 2019년에 글로벌 팬덤 플랫폼인 'Weverse' 사업을 시작하며 전 세계의 팬과 아티스트들이 커뮤니티로 모일 수 있는 공간을 마련했습니다. 자세히 읽기 고객 사례 소비자가 현명한 선택을 할 수 있도록 지원 폭발적으로 성장하는 비즈니스 데이터를 활용하기 위해 분석 및 AI를 점점 더 많이 적용하고 있습니다. 자세히 읽기 고객 사례 AI로 인한 신약 개발 과정 변화 AstraZeneca는 세계적으로 가장 치료가 어려운 난치병에 대한 혁신적인 치료제를 발견하여 개발 및 상용화합니다. 자세히 읽기 고객 사례 ML로 다시 태어난 모바일 뱅킹 세계 최대 규모의 국제적 은행 중 하나인 HSBC는 모바일 기기에서 디지털 결제를 관리하기 위한 새로운 방법을 모색하고 있습니다. 자세히 읽기모든 고객 둘러보기데이터 팀의 효과데이터 팀은 세상에서 가장 어려운 문제를 해결하기 위해 모인 팀입니다.방법 보기 →다음 성공 사례의 주인공이 되세요!문의리소스고객 사례Condé Nast에서 Databricks를 통해 고객에게 개인 맞춤형 콘텐츠를 제공한 방법을 알아보세요.자세히웨비나Apple과 Disney+에서 통합형 분석과 AI를 성공 수단으로 활용하는 법지금 시청하기팟캐스트Humana 선임 부사장(SVP), 최고 데이터 및 분석 책임자(CDAO)인 Slawek Kierner 님 전하는 데이터 + AI가 의료 서비스 형평성에서 수행하는 역할지금 시청하기시작할 준비가 되셨나요?무료 시험판사용해 보기문의제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티솔루션산업 기준프로페셔널 서비스솔루션산업 기준프로페셔널 서비스회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처Databricks 채용 확인하기WorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark 및 Spark 로고는 Apache Software Foundation의 상표입니다.개인 정보 보호 고지\|이용약관\|귀하의 개인 정보 선택\|귀하의 캘리포니아 프라이버시 권리
https://www.databricks.com/dataaisummit/faq	FAQ - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQA's to your Q'sWhat is Data + AI Summit?This year, Data + AI Summit will be both in-person and online, bringing together the open source community to explore all things data, analytics and AI — and how these are unified on the lakehouse. Join in-person in San Francisco to experience two keynotes, 200+ sessions, meetups, industry forums, an expo hall with over 100 sponsors, add-ons like hands-on training and certifications, and fun events like the Welcome Reception and Summit party. Learn more by exploring the Session Catalog or the Why Attend pages. Can’t make it to the in-person event? Join thousands of attendees online to view the two keynotes, 10live streamed breakout sessions and live interviews with Databricks executives and industry experts for the virtual event. When and where will the Data + AI Summit take place?Data + AI Summit will take place in San Francisco, CA at the Moscone Center, South during June 26 - 29. A few select Summit events will take place at the Intercontinental, San Francisco - a short walk from Moscone Center. Learn more about the in-person event and register now. How much does the in-person Data + AI Summit cost to attend? Are there any group or special discounts?A full conference pass costs $1,795. Group discounts are available for purchases of 4 or more and a special discount for GOV/EDU/NFP. Visit the pricing page for details. When and where will the free virtual event take place?The free Virtual Data + AI Summit will be held June 28 - 29 on https://www.databricks.com/dataaisummit/. Learn more about the free virtual event and register now. Will sessions be recorded and available after the event?Majority of the 200 breakout sessions delivered at the in-person event in San Francisco will be recorded and available on-demand on https://www.databricks.com/dataaisummit/. On-demand sessions can be accessed by registering for either the in-person and virtual events. These sessions will be available within a week of the live event. What topics and technologies will be covered and who are the speakers at the Data + AI Summit?With more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, lightning talks, industry forums, and more. Speakers include top experts, researchers and open source contributors from Databricks and across the data and AI community. Learn more by exploring the Session Catalog, Speaker and Why Attend pages. Can I pre-register or reserve a seat for sessions?There is no reserved seating or pre-registration for sessions. The most popular sessions will be repeated. Attendees can also plan ahead by viewing the session scheduler (available at the end of May) and creating their own custom agenda. What training course add-ons are available?Build and expand skills with pre-conference training. More than 15 instructor-led, hands-on training courses are available to be added on to your full conference pass. The trainings are either full or half-day, include both lecture, hands-on exercises and live Q&A and are available for all levels. See the full training schedule here. Training add-ons are available for a fee. View prices here. Sign up for training during your Summit registration or if you have already registered but didn’t add training, you can edit your registration details to add it at any time via the registration portal. Can I attend a training without attending the Summit?No. To sign up for trainings, you must select your desired course during registration or if you are already registered, you can add it any time via the registration portal. How do I qualify for a group rate for training?Group rates are offered to groups of four or more attendees registering for training together. Contact [email protected] to receive a group rate discount code. Will certification exams be available?Yes, we are offering the opportunity for in-person attendees to leverage complimentary Databricks certification exams ($200 USD value). The exams are 90-120 minutes long. The following Databricks certification exams qualify: Databricks Certified Associate Developer for Apache Spark™ 3.0 – Python Databricks Certified Associate Developer for Apache Spark™ 3.0 – Scala Databricks Certified Data Analyst Associate Databricks Certified Data Engineer Professional Databricks Certified Data Engineer Associate Databricks Certified Hadoop Migration Architect Databricks Certified Machine Learning Associate Databricks Certified Machine Learning Professional How do I make a change to my registration?If you need to update your registration, please send an email to the registration help desk. What is the cancellation policy?Substitutions Substitution requests can be processed in person onsite or via written request, please contact the Help Center. If requested in writing, please provide the names and emails of both the original and substitute registrants with both parties copied in the email. All requests for substitutions must be received no later than 5:00 PM (PDT) on June 23, 2023. Onsite substitutions will incur a US $50 processing fee. Cancellations The Databricks Registration Team must receive all cancellation requests in writing; please contact the Help Center by June 21, 2023. Refunds We will issue a full refund, minus a 10% fee, for written cancellation requests received on or before March 27, 2023 at 11:59 PM PDT. Cancellation requests received between March 28, 2023 and May 25, 2023 at 11:59 PM PDT, will be issued a 50% refund, minus a 10% cancellation fee. No refunds will be offered for paid items after May 26, 2023. Refunds will be processed 5 to 7 business days after the cancellation request has been processed and confirmed to the method of payment on the attendee record. If you have not received a refund by July 1, 2023, please contact the Help Center. Can someone attend in my place?Yes, if you are unable to attend please send an email to the registration help desk to initiate the substitution. Are there hotel blocks available?Yes, Databricks has reserved hotel blocks for Data + AI Summit. During your registration process, you will have the opportunity to book your room. Inventory is limited, available on a first-come, first-booked basis, and our discounted rates are only available until June 1 so book now in the attendee portal. Reserved hotel blocks are available at The Canopy, Hyatt Regency Soma, Intercontinental, Marriott Union Square, Parc 55, The Clancy, The W and Westin St Francis. What prices are secured for attendees looking to book a hotel? Hotel Group Rate W Hotel $349 Parc 55 $309 The Clancy $339 JW Marriott $329 Marriott Union Square $309 St Regis $565 Hyatt Downtown SOMA $329 Intercontinental $365 Westin St Francis $359 Hilton San Francisco $309 How do I make changes to an existing hotel reservation?Attendees may access their existing reservation to make changes via their confirmation email. Please click on the registration link within the email and make desired edits. Please remember to submit your changes. What is the hotel cancellation policy?The cancellation policy varies from property to property; typically 24 or 72 hours. Each cancellation policy is published within the housing portion of the registration. After the cancellation deadline has passed, attendees will be charged for the cost of one room night should they cancel or postpone their arrival date. If I cancel my Summit registration, can I transfer my hotel reservation to another attendee?No. Credit card data may not transfer from one attendee to another, which makes transferring hotel confirmations from one to another not feasible. Can I book multiple rooms on my registration for myself and a colleague?Attendees may book only one hotel reservation under their registration. What if I don’t check in on my scheduled arrival date?Guests who do not arrive on their confirmed check-in date will be charged a no-show fee by the hotel property, equal to (1) nights rate. Do I need a credit card to reserve a room?Yes. All attendees must provide a credit card in order to secure a guest room. Can I contact the hotel directly to make a hotel reservation and receive the discounted Summit rate?The group rate is available through group registration only. Can I contact the hotel directly to change my existing reservation?Please make edits to your reservation directly in the registration so that when the hotel pulls your reservation information, they capture all changes you require. Only after the hotel cut-off date (June 1 or June 9, depending on the property you secure) can you contact the hotel directly for changes. When will I receive my hotel confirmation?Hotel confirmations will be shared on June 16th. I want to arrive earlier/stay later than the system is showing as available. How can I adjust my reservation?Guest room inventory within the registration platform is based on first come/first serve. You are welcome to secure your extension directly with the hotel (at rack rate) and then ask the hotel to “link” your two reservations. You may also secure your own reservation, including your early/late stay dates, at a property outside of what is offered on the group registration. What are the health protocols in place for the Data + AI Summit?The health of our attendees is very important to us. As of now, we are not requiring vaccinations or masks. We acknowledge this is an ever-changing landscape and we are deeply committed to staying abreast of updated guidance from the Centers for Disease Control and Prevention (CDC) and federal, state, and local governments. Databricks reserves the right to adjust these protocols if guidance changes. What are the safety and security protocols in place for the Data + AI Summit?Your safety at the event is our top priority. You will likely see a strong security presence, and there will also be many people working behind the scenes to help keep you safe. We’re prepared to respond to incidents in partnership with local, state, and federal authorities. Everyone will be required to show an ID when checking in at registration and will be required to wear their badge for all Data + AI Summit official events. We’ll have metal detectors at the entrances to Moscone South. All bags will be subject to search upon entering any conference site. Are there any items I can’t bring to the event?Prohibited items within the event space and after hours event space include, but are not limited to: Weapons, firearms, or knives (regardless of size) or items that can be mistaken as a weapon. Pets or other animals, except approved service animals. Service animals should remain on a leash or in a harness and under the control of the owner at all times. Personal mobility devices (with or without a motor) unless for ADA use. This includes but is not limited to: skateboards, hoverboards, bicycles, scooters, uniwheels, and all similar products. No smoking (including e-cigarettes) is allowed within the facility. Poles and sticks; selfie sticks. Laser lights, laser pointers. Mace/pepper spray, tasers, stun guns, or similar devices. Sharp and/or pointed objects: razor blades, scissors, knitting needles, screwdrivers, etc. Whistles, noisemakers, and/or sound/voice enhancement devices, such as bullhorns. Banners, signs, or placards unless authorized by production or security management. Flashlights, unless authorized by production or security management. Wi-Fi and/or Bluetooth signal disruptors. Tripods for cameras (does not apply to media). Inflatable items (e.g., balloons). Drones, unless authorized by production or security management. No outside alcohol. No illegal substances. Can I participate as a sponsor in the event?If you are interested in sponsorships or have any sponsorship questions, please contact [email protected]. When and how will I receive more information about how to navigate the in-person event in San Francisco?We will be launching a mobile app at the beginning of June. The mobile app will include everything needed to navigate the event including information about meals, transportation, map, agenda and more. We will be sending out a series of emails along with the mobile app launch, which will help you make the most of your experience at Summit. What is the Data + AI code of conduct and event policies?We are committed to fostering Diversity, Equity and Inclusion. We will continue to create an inclusive event where everyone can learn, collaborate, and build community. Code of Conduct Event Policies Privacy Notice I still have some unanswered questions. Who can I contact?Send any other questions to the help desk. HomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/glossary/overall-equipment-effectiveness	Overall Equipment EffectivenessPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWOverall Equipment EffectivenessAll>Overall Equipment EffectivenessTry Databricks for freeGet StartedWhat is Overall Equipment Effectiveness?Overall Equipment Effectiveness(OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to run. It identifies the percentage of manufacturing time that is truly productive. An OEE is a dashboard that shows the total performance of a discrete or continuous process. OEE is maximized at 100% and means that only good parts are produced (100% quality), at the maximum speed (100% performance), and without interruption (100% availability).Measuring OEE is a manufacturing best practice. By measuring OEE and the underlying losses, important insights can be gained on how to systematically improve the manufacturing process. OEE is an effective metric for identifying losses, bench-marking progress, and improving the productivity of manufacturing equipment (i.e., eliminating waste).Why Is this important?OEE has been used as the prime manufacturing metric for decades. Historically, OEE monitoring used manual data collection directly from the machines on a batch basis and calculated the metric. In itself, OEE is a reactive dashboard that monitors the past and historical performance - the true power of OEE is to guide to implement use cases that improve the components of OEE - the deployment of predictive maintenance to improve availability, or quality control leveraging computer vision to improve quality that are predictive in function.What are Databricks’ differentiated capabilities?Databricks’ Lakehouse uses technologies that include Delta, Delta Live Tables, Autoloader and Photon to enable customers to make data available for real-time decisions.Lakehouse for MFG supports the largest data jobs at near real-time intervals. For example, customers are bringing nearly 400 million events per day from transactional log systems at 15-second intervals. Because of the disruption to reporting and analysis that occurs during data processing, most retail customers load data to their data warehouse during a nightly batch. Some companies are even loading data weekly or monthly.A Lakehouse event-driven architecture provides a simpler method of ingesting and processing batch and streaming data than legacy approaches, such as lambda architectures. This architecture handles the change data capture and provides ACID compliance to transactions.Delta Live Tables simplifies the creation of data pipelines and automatically builds in lineage to assist with ongoing management.The Lakehouse allows for real-time stream ingestion of data and analytics on streaming data. Data warehouses require the extraction, transformation, loading, and additional extraction from the data warehouse to perform any analytics.Photon provides record-setting query performance, enabling users to query even the largest of data sets to power real-time decisions in BI tools.What data challenges need to be addressed to build predictive OEE capabilities?Handling the volume and variety of IoT data—To enable predictive use cases embedded in OEE manufactures, the Lakehouse handles all types of diverse data structures and schemas, including everything from intermittent readings of temperature, pressure, and vibrations per second to handling fully unstructured data (e.g., images, video, text, spectral data) or other forms such as thermographic or acoustic signals, from the edge delivered through diverse supported drivers and protocols.Managing the complexity of real-time data: In order to drive continuous process monitoring, throughput optimization or predictive maintenance, the Lakehosue enables real-time analytics on streaming data. The lakehouse effectively ingests, stores, and processes streaming data in real time or near-real time in order to instantly deliver insights and action.Freeing data from independent silos—Specialized processes (innovation platforms, QMS, MES, etc) within the value chain reward disparate data sources and data management platforms that tailor to unique siloed solutions. These narrow point solutions limit enterprise value by considering only a fraction of the insight cross-enterprise data can offer, in addition, duplicate siloed solutions divide the business, limiting collaboration opportunities. Also, the Lakehouse ingests, stores, manages, and processes streaming data from all points in the value chain, combines it with Data Historians, ERP, MES and QMS sources and leverages it into actionable insights.Diverse analytical capabilities—Legacy data warehouses offer limited ability to provide insights and analytics into platform usage and performance. For Connected Manufacturing IoT solutions, the Lakehouse provides a wide range of analytical options—including everything from SQL analytics and search capabilities, to tools to support machine learning and modeling, along with tight integration with leading business intelligence (BI) solutions that offer specialized dashboard and business analytics capabilities.Predictive modeling capabilities—Predictive modeling capabilities are key to delivering insights, and the Lakehouse provides notebook driven machine learning capabilities used to predict and prevent disturbances before they impact operations.Additional ResourcesDatabricks solutions for ManufacturingBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/dataaisummit/speakers?itm_data=hp-hamburger-speakers-dais23	Speakers - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSpeakersBrowse the roster to find new and familiar faces alike. The Data + AI Summit draws experts from all over the globe across a wide array of fields. Featured speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAll speakersAayush PatelData & Platform EngineerSkywatchAbhishek PatelHead of Databricks COELTIMindtreeAdam WilsonCo-Founder, Chief of ProductDivirod, Inc.Adi PolakData & AI TechnologistTechnologistAdriana IspasStaff Product ManagerDatabricksAikaterini KalouPrincipal Data ScientistCitrixAjali SenSenior ManagerAccentureAjmal AzizSolutions ArchitectDatabricksAkira AjisakaSenior Software Development EngineerAmazon Web ServicesAlain BrianconVP Data Science Profiles by KantarKantar GroupAlbert HuSenior Analytics EngineerRec RoomAlessandro GaravagliaLead ML EngineerGucciAlexander BoothAssistant Director of Research & DevelopmentTexas Rangers Baseball Club, LLCAlexander VanadioPrincipal ConsultantOptivAli GhodsiCo-founder and CEODatabricksAlon GubkinCo-Founder & CTOAporiaAman KapoorHead of Data PlatformPetronasAmanda MilbergSenior Partner Sales EngineerDataikuAmine BenhamzaLead Solutions ArchitectDatabricksAmir SkovronikDistinguished Software EngineerAkamaiAmrinder Singh OberaiEMR Migrations LeadDatabricksAnanya GhoshBusiness Application Owner for DatabricksNationwide InsuranceAndrew BlanceInnovation ConsultantWaterstonsAndria FuquenTechnical Program ManagerImmutaAndy HanksSenior Data Architect, Analytics PlatformCRISP Shared ServicesAnfisa KaydakVP, Data Product & EngineeringHealthverityAngela ChuSenior Solution ArchitectDatabricksAnil PuliyerilSenior ArchitectHabuAnindita MahapatraLead Solutions ArchitectDatabricksAnindya SahaML Platform Software EngineerAnkit MathurTech Lead, Model Serving GPUsDatabricksAnna RussoGlobal Director of Data ScienceGucciAnton OkolnychyiSoftware EngineerAppleAntoni BaumSoftware EngineerAnyscaleAntonio CasteloCollibraAnup SeguCo-Head of Data EngineeringYipitDataArtem MeshcheryakovConsultantORAYLIS GmbHArthur LiSenior Software EngineerInstacartArujit PradhanSoftware EngineerCoinbaseArun PamulapatiSr. Staff Security Field EngineerDatabricksAshwin GangadharSenior Solutions ArchitectMongoDBAtiyah CurmallyPrincipal Environmental SpecialistInternational Finance CorporationAustin FordStaff Product ManagerDatabricksAvinash SooriyarachchiSenior Solutions ArchitectDatabricksBalaji RamanujamAVP - Senior Principal Technology ArchitectInfosysBasak EskiliML EngineerAhold DelhaizeBehzad BordbarLead Data ScientistMarks & SpencerBeinan WangSenior Staff Software EngineerAlluxioBen CoppersmithSr. Manager, Data PlatformDisney StreamingBen WilsonPrincipal Specialist Solutions ArchitectDatabricksBeth MattsonSenior Data EngineerOur Family WizardBin MuVice President and Head of Data & AnalyticsAdobeBinwei Yangsoftware engineerintelBlaise SandwidiLead Data Scientist, As. ESG Officer, PhDInternational Finance Corporation (IFC)–World Bank GroupBob ZhangSenior Technical Program ManagerMicrosoftBrad CorwinChief Data ScientistBooz Allen HamiltonBradley AxenMachine Learning EngineerBlockBrendan BarsnessData and Analytics ArchitectDeloitteBrooke WenigDirector, Machine Learning PracticeDatabricksCan ElfeogluStaff Product ManagerDatabricksCelia KungEngineering ManagerDatabricksChang SheCEOLanceDBChao SunSoftware EngineerAppleChen GuoStaff Software EngineerCoinbaseChris StevensSenior Staff Software EngineerDatabricksChris VoLead Member of Tech StaffAT&TChris InkpenSolutions architectHoneywellChris HechtDatabricksChris MantzData ArchitectSlalomChristian AcuñaSenior Data EngineerGrammarlyChristian HamiltonDirector, Data Science Technology84.51Christina TaylorData EngineerToptalChristina TaylorSenior Staff Data EngineerCatalyst SoftwareChristopher LocklinEngineer Manager, Data PlatformGrammarlyChunxu TangResearch ScientistAlluxioCody FergusonData & AI Management Branch ChiefChief Digital and Artificial Intelligence Office - AdvanaCorey ZumarSoftware EngineerDatabricksCorey ZwartChief Technology OfficerPumpJack DataworksCort LunkeData & Analytics Lead - TruterraLand O'LakesCraig WileySr. Director of Product, Lakehouse AIDatabricksCyrielle SimeonePrincipal Product Marketing ManagerDatabricksDael WilliamsonField CTODatabricksDan HoustonManager, Data Science and Exploration Advanced AnalyticsUSPSDan SmithHead of Technology Data & AnalyticsPerenti GroupDanica FineSenior Developer AdvocateConfluentDaniel TenedorioSr. Staff Software EngineerDatabricksDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL)MITDarshana SivakumarStaff Product ManagerDatabricksDarth VaderSith LordThe Galactic EmpireDatin Ts. Habsah Binti NordinChief Data OfficerPETRONASDavid SkinnerChief Strategy OfficerAcxiomDavid TempelmanResident Solutions ArchitectDatabricksDawn SongProfessor, Department of Electrical Engineering and Computer ScienceUC BerkeleyDeepa ParanjpeDirector of EngineeringDiscoveryDeepak SekarSr. Solution ArchitectDatabricksDenny LeeSr. Staff Developer AdvocateDatabricksDerek SlagerCTOAmperityDerek SugdenAd Measurement Lead – Measurement & AttributionEffectvDevlina DasSenior Software EngineerInstacartDeylo WooData Engineer ArchitectProvidence Health ServicesDilip BiswalSenior ArchitectAdobeDillon BostwickSolutions ArchitectDatabricksDipankar MazumdarDeveloper AdvocateDremioDon ScottVP, New Product DevelopmentHitachi Solutions AmericaDon Bosco DuraiCofounder and CTOPrivaceraDonghwa KimSr. Director of IT ArchitectureOntada, a McKesson CompanyDouglas MooreLead Specialist Solutions ArchitectDatabricksDurga KalaSr. DirectorVisa Inc.Egor GryaznovCTO and Co-founderBigeyeEllen SulcsDirector, Data Products & EngineeringT-MobileEllie HajarianSnr IT ManagerTD BankElliot ShmuklerCo-Founder & CEOAnomaloEmad MostaqueCEOstability.aiEric PeterSr Staff Product ManagerDatabricksEric SchmidtFormer CEO and Chairman, Google; Co-FounderSchmidt FuturesErika EhrliSenior Director of Product MarketingDatabricksErin BoelkensVP of ProductLiveRampErni DurdevicSpecialist Solutions Architect (Geospatial)DatabricksFabian JakobsSr Staff Software EngineerDatabricksFabien CochetIT Expert on Data and AnalyticsMichelinFabio Luis Correia da SilvaArchitecture SpecialistBradescoFaraz YasrobiSoftware EngineerGrammarlyFrancisco RiusHead of Data Science and Data EngineeringMinecraft at MicrosoftFranco PatanoProduct SpecialistDatabricksFrank MunzPrincipal Technical Marketing EngineerDatabricksGanesh DeivarayanSr ManagerAmerican AirlinesGaurav SarafProduct ManagerDatabricksGavita RegunathPrincipal Data ScientistAdvancing AnalyticsGeoffrey FreemanSolutions ArchitectT-MobileGidon GershinskyLead Systems ArchitectAppleGilad AsulinBig Data Engineer Team LeaderAkamai Technologies, IncGreg NelsonVP of Data OperationsHighmark HealthGreg KroleskiProduct ManagementDatabricksGregory LittleDCDAO for Enterprise Platforms and Business OptimizationDoD CFO Transformation OfficeHannes MühleisenCo-Founder and CEODuckDB LabsHao ZhuSenior ManagerNVIDIAHari ShankarSenior Director, R&DVizioHari RajaramSr Director / Principal Data ArchitectProcoreHarrison ChaseCEOLangChainHarsh MishraLead Enterprise ArchitectAustralian Rail Track CorporationHeiko UdluftChief Technology OfficerDivirod, Inc.Himanshu AroraResident Solutions ArchitectDatabricksHimanshu RajaDatabricksHitesh SahniHead of Cloud Data Platforms and Data Engineering SolutionsDeutsche Post DHLHolly SmithSenior Resident Solutions ArchitectDatabricksHuaxin GaoSoftware EngineerAppleHyukjin KwonStaff Software EngineerDatabricksIan SotnekDirector of ProductAI Squared, IncIan GallowaySenior Director, ApplicationsCollins AerospaceIfigeneia DerekliField Engineering Manager & Unity Catalog SpecialistDatabricksIoannis PapadopoulosCloud TechnologistDatabricksItai YaffeSenior Big Data ArchitectAkamaiIvan PengSoftware EngineerDoorDashJacek LaskowskiIT Freelancerjapila.plJackie BrosamerDirector of Software EngineeringBlockJacob RennChief TechnologistAI Squared, IncJacolon WalkerCo-founder & CTOMonadJaison DominicSenior Manager Information SystemsAmgenJames DemmelDr. Richard Carl Dehmel Distinguished ProfessorUniversity of California, BerkeleyJames NormanPrincipal Software EngineerNikeJamie BakerDirector of ProductMatillionJason ShiverickData Platform ManagerRivianJay BhankhariaSenior Director, Data PartnershipsDatabricksJay YangPrincipal Data EngineerProcoreJeff Breeding-AllisonSenior Data ScientistMars PetcareJeff MrozTechnical SME for Cloud and Big DataWoolpert / US Army Corps of EngineersJeffrey HessLead TechnologistBooz Allen HamiltonJeffrey ParkinsonVP, Core Data EngineeringNorthwestern MutualJeffrey ChouCo-Founder, CEOSync ComputingJegadeesan PugazhenthiLead Big Data EngineerAT&TJeremy LewallenProduct ManagerDatabricksJiajun YaoSoftware EngineerAnyscaleJim HibbardSenior Developer AdvocateDatabricksJim ThorstadSolutions ArchitectDatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchUniversity of California at BerkeleyJoanna GurryExecutive, Data DeliveryNational Australia Bank (NAB)Joe WalshDirector of Measurement & AttributionEffectvJohn RousselCIOCalifornia Department of Public Health (CDPH)John ThompsonGlobal Head, Artificial IntelligenceEYJohn KutayDirector of Product ManagementStriimJon OsbornField CTOAscend.ioJonathan KellerSr. Director, Product ManagementDatabricksJonathan HollanderVP, Enterprise Data Technology PlatformsTD BankJonathan NeoData EngineerCanvaJordan PeckPrincipal Technical Account ManagerSnowplowJordan DonmoyerManager, Customer Data SolutionsThe Hershey CompanyJoseph SarsfieldMachine Learning EngineerMarks & SpencerJoseph BradleyLead Product SpecialistDatabricksJules DamjiLead Developer AdvocateAnyscaleJulie FerrisVice President, Commercial OptimizationDefinitive HealthcareJulien Le DemChief ArchitectAstronomerJun Rong LauData Engineer/AnalystGrabTaxi Holding Pte LtdJunta NakaiRVP, Industry Solutions, Financial Services and SustainabilityDatabricksJustin BreeseSr. Product ManagerDatabricksJustin DeBrabantSVP of ProductActionIQJustin LaiDistinguished Data ArchitectBlackBerryJustin ThompsonDirector, IT Data and AnalyticsJetBlueKarthik RamasamyHead of StreamingDatabricksKasey UhlenhuthStaff Product ManagerDatabricksKeith AndersonSolution PrincipalHitachi SolutionsKeshav SanthanamPhD StudentStanford UniversityKetan GanatraSolution ArchitectDatabricksKieran TaylorSenior Software Engineer IIInstacartKrishti BikalSenior Executive - Director BI & AnalyticsEmeraldKyle HaleProduct SpecialistDatabricksKylie TaylorData ScientistMars PetcareLakhan PrajapatiDirector of Architecture and EngineeringZS associatesLarry FeinsmithHead of Global Tech Strategy, Innovation and PartnershipsJP Morgan Chase & Co.Lee YangSr. Principal SW EngineerNVIDIALeena DalviAssistant Vice President, Enterprise Data & AnalyticsNavy Federal Credit UnionLeo DuncanSr. Solutions ArchitectKyvos Insights Inc.Leon EllerSolutions ArchitectDatabricksLewis MbaeHead of Customer EngineeringRudderStackLin QiaoCo-creator of PyTorch, Co-founder and CEOFireworksLindsay MicoHead of Data ScienceProvidence HealthLindsey WoodlandExecutive Vice President, Client Data Science605Lior GavishCTO and Co-founderMonte Carlo DataLiping HuangSenior Solutions ArchitectDatabricksLorenzo De TomasiData Architect, Data Platforms Lead at BarillaBarilla G. e R. Fratelli S.p.A.Lucas dos Santos CelestinoPlatform Product ManagerAB InbevLuk VerhelstData ArchitectVolvo Group (consultant)Luyang WangLead Distinguished ScientistVerizonMacGregor WinegardAssociate Data EngineerKPMGMaciej SzpakowskiCo-founderProphecyMadalina TanasieChief Technology OfficerCollibraMaggie DavisPrincipal, Data EngineeringSlalomMahesh PrakriyaDirector in Intelligence PlatformMicrosoftMalav ShahSenior Data ScientistDIRECTVManbir PaulVP of Engineering, Data Insights and MarTechSephoraMani KandasamyTech FellowDeloitte Consulting LLPManu SharmaCEOLabelboxMarcel KramerHead of Data EngineeringABN AMRO Bank N.VMaria VechtomovaML EngineerAhold DelhaizeMaria DaibertData Platform Product ManagerAB InbevMarianna CervinoGlobal Data ScientistGucciMarius PangaSolutions ArchitectDatabricksMark LeeSenior Specialist Solutions ArchitectDatabricksMark D'AndreaGlobal Chief Revenue OfficerAccuweatherMartin GrundSenior Staff Software EngineerDatabricksMat KeepSenior Director, MongoDB Products TeamMongoDBMatei ZahariaCo-founder and Chief Technologist; Original Creator of Apache Spark™ and MLflowDatabricksMatt McKenzieGM, TechnologyTabcorpMatteo QuattrocchiDirector, Policy-EMEABSAMatthew HayesVice President of SAP BusinessQlikMatthew PowersDeveloper AdvocateDatabricksMatthew HayesSoftware EngineerDatabricksMatthew DoxeySenior EpidemiologistWashington State Department of HealthMatthew KarasickChief Product OfficerHabuMaxime AgostiniCEOSarus Technologies IncMeena RamSr Director, Enterprise Data and Records Management OfficeCIBCMegan FogalSolutions ArchitectDatabricksMenglei SunSenior Software EngineerDatabricksMiao WangSenior Engineering ManagerAdobeMichael ShtelmaLead Specialist Solutions ArchitectDatabricksMichael ArmbrustDistinguished EngineerDatabricksMichael GreenSenior Data ScientistHitachi Solutions AmericaMichael CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyMichael PowellChief, Registry & Assessment Section Immunization Branch Division of Communicable Disease Control Center for Infectious DiseasesCalifornia Department of Public Health (CDPH)Michael SankyRVP, Industry Solutions, Healthcare and Life SciencesDatabricksMike ConoverSoftware EngineerDatabricksMike TangAssociate Director, Responsible AIVerizonMike Del BalsoCo-founder + CEOTectonMilos ColicTech Lead EMEA Public Sector - Sr. Solutions ArchitectDatabricksMiranda LunaProduct ManagementDatabricksMitch ErtlePartner Solutions EngineerSigma ComputingMohan KolliIT DirectorLabCorpMorgan HsuDirector, Data and ML EngineeringFanDuelMostafa MokhtarPrincipal Software EngineerDatabricksMurali MadireddiArchitectAccentureNabil RaadSVP of Data and AnalyticsGM FinancialNadine FarahHead of Dev RelOnehouseNaresh YegireddiStaff Data EngineerIndigo AGNat FriedmanCreator of Copilot; Former CEOGithubNatalia DemidovaDirector-Solution Principal, Data Science and Artificial Intelligence, North AmericaHitachi Solutions America Ltd.Naveen ZutshiChief Information OfficerDatabricksNeil PatelLead Specialist Solutions ArchitectDatabricksNic JansmaSenior Principal Lead EngineerAkamaiNicholas WoodbrigeSenior Director Commercial Data & Digital Architecture Commercial Products, Analytics, TechnologyGlaxoSmithKlineNick KingFounder & CEOData KineticNicolas PelaezTechnical MarketingDatabricksNihar ShethSenior Product ManagerAWS - AmazonNitu NiveditaManaging DirectorAccentureNoam BresslerML Team LeadDeepchecksNoritaka SekiyamaPrincipal Big Data ArchitectAmazon Web ServicesOliver DykstraData EngineerTexas RangersOnik KurktchianHead of S&P Global Marketplace WorkbenchS&P GLOBALOri ZoharPrincipal Product Marketing ManagerDatabricksOz KatzCTO @ Treeverse, co-creator of lakeFSTreeverse LTDPakshal Kumar H DhelariaSenior Software Engineer 1CitrixPamela PettitSolutions ArchitectDatabricksParth ChandraSoftware EngineerApplePascal van BellenSenior ConsultantORAYLIS GmbHPatrick HallPrincipal Scientist \| Visiting FacultyBNH.AI \| GWUPaul RoomeStaff Product ManagerDatabricksPaul MracekSenior Solutions ArchitectDatabricksPaul WellmanVP, Executive Product Owner, Data-as-a-ServiceTD BankPaul MarshSenior Director Application DevelopmentNew York JetsPaula MartinezCEO & CofounderMarvikPearl UbaruSr. Technical Marketing EngineerDatabricksPedro BoaretoChapter Leader of Analytics EngineeringBradescoPercy LiangProfessor of Computer ScienceStanfordPhilippe LeonhartDigital Transformer, Corporate Business ServicesMichelinPieter NoordhuisSr. Staff Software EngineerDatabricksPouya Barrach-YousefiData Pro and Director Strategic AccountsProphecyPrashanth BabuLead Product SpecialistDatabricksPrateek ChawlaFounding EngineerMonte CarloPraveen VemulapalliDirector- TechnologyAT&TPravin DarbareVice President of Data AnalyticsWorkdayPritesh PatelPublic Sector Leader, UK&IDatabricksPulkit ChadhaSr. Solutions ArchitectDatabricksRafael BarcelosSoftware ArchitectMicrosoft CorporationRafi KurlansikLead Solutions ArchitectDatabricksRaghu JayachandranSenior Manager Enterprise DataRaceTrac Inc.Rahil BhatnagarDevelopment Lead, LOLAAnheuser BuschRahul PandeySolution ArchitectadidasRajesh IyerVice President Financial Services Insights & DataCapgeminiRakesh KumarStaff Software EngineerLyft IncRakesh SinghLead ArchitectABN AMRO Bank N.VRashmi KansakarDirector, Data & Cloud Architect84.51Rekha BachwaniEngineering Director, ML EngineeringThe Walt Disney CompanyReynold XinCo-founder and Chief ArchitectDatabricksRicardo PortillaPrincipal Solution ArchitectDatabricksRisha RavindranathSr Manager, Data GovernanceComcast AdvertisingRob SakerGlobal VP, Retail and ManufacturingDatabricksRobin SutaraField CTODatabricksRobinson CreightonPrincipal Analyst, Enterprise Data OpsComcast AdvertisingRodrigo BeceiroCTO & CofounderMarvikRoger DunnCo-founder, CTOExponamRoie Schwaber-CohenStaff Developer AdvocatePineconeRomit JadhwaniSr. Director, Data Analytics, Engineering and IntegrationsDatabricksRong MaSoftware EngineerintelRuifeng ZhengSenior Software EngineerDatabricksRyan BoydCo-founderMotherDuckRyan HarrisPrincipal Cybersecurity EngineerHSBCRyan JohnsonSenior Staff EngineerDatabricksSaad AnsariSenior Staff Product ManagerDatabricksSachin Balgonda PatilSolutions ArchitectDatabricksSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSai RavuruSenior Manager of Data Science & AnalyticsJetBlueSamrat RaySenior Staff Product ManagerDatabricksSanjeev KumarVice President, Data Analytics and AIGainwell TechnologiesSanket AminSenior Manager of CAS Data Science and AnalyticsCollins AerospaceSarah PollittGroup Product ManagerMatillionSatish GarlaSr Solutions ArchitectDatabricksSatya NadellaChairman and CEOMicrosoft, Live Virtual GuestScott MeierDirector, Data Analytics Service, Financial Services CenterU.S. Department of Veterans AffairsScott StarbirdGeneral Counsel, Public Affairs and Strategic PartnershipsDatabricksScott BellPrincipal Consultant and Databricks SMERapidDataScott CastleChief Strategy OfficerSisenseSean KnappFounder & CEOAscend.ioSean OwenPrincipal Product SpecialistDatabricksSeth BabcockHead of Connected Aviation Tech Ops Solutions and AnalyticsCollins AerospaceShasidhar ErantiSpecialist Solutions ArchitectDatabricksShawn GilleranPrincipal Cloud Solutions LeadLiveRampShawn BenjaminData and Business Intelligence ChiefU.S. Department of Homeland Security - USCISShir ChorevCTODeepchecksShiv TrisalGTM Director, Manufacturing & EnergyDatabricksSiddharth BhaiSr. Manager, Product ManagementDatabricksSidharth KunnathPrincipal ArchitectAmerican Airlines, IncSimon WhiteleyCTOAdvancing AnalyticsSirui SunDatabricksSlava FridCTOWorldQuant PredictiveSneh KakiletiVice President, Product ManagementZoomInfoSpencer CookSenior Solutions Architect - Financial ServicesDatabricksSreekanth RatakondaPrincipal Solutions ArchitectLabcorpSridhar DevarapalliSenior Director, Product ManagementDatabricksSrinivasa KanamathaSenior ManagerBlackBerryStan LinSenior Software EngineerMicrosoft CorporationStefania LeoneSr. Manager Product ManagementDatabricksStephen SheltonVice President, Business IntelligencePluto TVSteve MahoneySr Manager, Product ManagementDatabricksSteve SobelGlobal Lead - Communications, Media & EntertainmentDatabricksSteven YuPrincipal Solutions ArchitectDatabricksSumesh NairDirector of Engineering, Data and Cloud StrategyOptum, United HealthGroupSuneel KonidalaSr. ManagerAccentureSunil RanganathanDirector, MLOPsTredenceSuresh MatlapudiLead Solutions Architect and Specialist SME, MigrationsDatabricksSurya TuragaSr. Solutions ArchitectDatabricksSuze HowseHead of Enterprise DataMarks and SpencerTanmay KumarSenior ManagerDeloitte Consulting LLPTathagata DasDatabricksTaylor HosbachData ScientistDIRECTVTeja TangedaPrincipal Data EngineerAmerican AirlinesTEST BecknerTESTTESTTest1 TestCFP1102testThet KoPrincipal Data EngineerSEEKThomas La PianaSenior Software EngineerEthycaThomas RoachSr. Solutions ArchitectDatabricksThorsten JacobsSr. Solutions ArchitectDatabricksTianyu LiuLead Data Scientist (Analytics)GrabTimothy AhrensMessaging Design Division ChiefDepartment of StateTodd GreensteinProduct ManagerDatabricksTomer PatelSoftware Engineering ManagerAkamai TechnologiesTony WangPhD studentStanfordUri MayHuntersVadivel SelvarajStaff Software EngineerRivianVarun SharmaPrincipal Data EngineerVisa Inc.Vicky AndonovaManager, Applied Machine LearningAnomaloVika SmilanskyDirector of Product MarketingThoughtSpotVikas Reddy AravabhumiStaff Backline EngineerDatabricksVincent ChenDirect of Product / Founding EngineerSnorkel AIVinit DoshiSenior ManagerTredenceVinod MarurSVP of EngineeringDatabricksVolker TjadenManager Solution ArchitectsDatabricksVuong NguyenSenior Solutions ArchitectDatabricksWassym BensaidSr. Vice President, Software DevelopmentRivianWeston HutchinsProduct ManagerDatabricksWill GirtenSr. Specialist Solutions ArchitectDatabricksWilliam ZanineHead of Data Management, Channel and Specialty North AmericaIQVIAWilly LulciucSr. Software EngineerAstronomerXiao LiSenior Engineering ManagerDatabricksXuefu WangSr. Data ScientistThe Trade DeskYali SassoonCPOSnowplowYang YouPresidential Young ProfessorNational University of SingaporeYaniv KundaSenior Software ArchitectAkamaiYaron SingerCEO & Co-FounderRobust IntelligenceYeshwanth VijayakumarSr Engineering Manager/ArchitectAdobeYoung BangPrincipal Deputy Assistant Secretary of the Army for Acquisition, Logistics and TechnologyU.S. ArmyYuki SaitoTechnical EvangelistNTT DATA CorporationZachary BannorData Engineering ManagerCondé NastZachary HuangPhDColumbia UniversityZaheera ValaniSenior Director of EngineeringDatabricksZeashan PappaSenior Product Specialist - Data GovernanceDatabricksZoe DurandSenior Product ManagerDatabricksSee the best of Data+AI SummitWatch on demandHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. 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https://www.databricks.com/dataaisummit/speaker/amrinder-singh-oberai	Amrinder Singh Oberai - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmrinder Singh OberaiEMR Migrations Lead at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/br/company/diversity	Diversidade e inclusão \| DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernança de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePreçosMarketplaceTecnologia de código abertoCentro de segurança e confiançaWEBINAR Maio 18 / 8 AM PT Adeus, Data Warehouse. Olá, Lakehouse. Participe para entender como um data lakehouse se encaixa em sua pilha de dados moderna. Inscreva-se agoraSoluçõesSoluções por setorServiços financeirosSaúde e ciências da vidaProdução industrialComunicações, mídia e entretenimentoSetor públicoVarejoVer todos os setoresSoluções por caso de usoAceleradores de soluçãoServiços profissionaisNegócios nativos digitaisMigração da plataforma de dados9 de maio \| 8h PT Descubra a Lakehouse para Manufatura Saiba como a Corning está tomando decisões críticas que minimizam as inspeções manuais, reduzem os custos de envio e aumentam a satisfação do cliente.Inscreva-se hojeAprenderDocumentaçãoTreinamento e certificaçãoDemosRecursosComunidade onlineAliança com universidadesEventosData+AI SummitBlogLaboratóriosBeaconsA maior conferência de dados, análises e IA do mundo retorna a São Francisco, de 26 a 29 de junho. ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConexão de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSoluções para parceirosConecte-se com apenas alguns cliques a soluções de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de AdministraçãoBlog da empresaImprensaDatabricks VenturesPrêmios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como líder pelo segundo ano consecutivoObtenha o relatórioExperimente DatabricksAssista às DemosEntre em contatoInício de sessãoJUNE 26-29REGISTER NOWO futuro dos dados está aberto a todosDiversidade, Equidade e Inclusão na DatabricksImpulsionado por dados. Desenvolvido por pessoas.Temos a missão de diversificar o big data, começando com nossa equipe. Acreditamos que origens, experiências, perspectivas, insights e habilidades diferentes alimentam a inovação e aprofundam nossa conexão uns com os outros e com nossos clientes. Nós nos esforçamos para cultivar uma cultura de pertencimento onde todos são capacitados para fazer o melhor trabalho de suas carreiras. De garantir pagamento igual para trabalho igual até criar uma programação que celebra, educa e eleva nossa equipe, Diversidade, Equidade e Inclusão (DEI) estão presentes em tudo o que fazemos.Certificação Fair Pay Workplace Temos orgulho de ser uma das seis primeiras organizações com certificação Fair Pay Workplace. Como parte dos esforços para alcançar a paridade salarial, a Databricks passou por uma avaliação rigorosa de nossos dados e práticas salariais e se comprometeu a permanecer responsável por meio de análises contínuas de equidade salarial.Gaingels e Flucas Ventures Nosso compromisso com a diversidade, a equidade e a inclusão (DEI) envolve toda a nossa equipe, das pessoas que trabalham conosco até as que investem em nós. É por isso que temos orgulho de fazer parceria com uma série de investidores de classe mundial, incluindo a Gaingels e a Flucas Ventures, que financiam empresas com um profundo compromisso com a DEI."Sabemos que, quanto mais dados tivermos, melhores serão os nossos insights. O mesmo acontece com a diversidade e a inclusão; a Databricks prospera ao incluir a maior diversidade possível de origens, experiências e pontos de vista."— Ali Ghodsi, cofundador e CEO da DatabricksNossas comunidadesAcreditamos que capacitar nossos funcionários é essencial para liberar todo o nosso potencial. Os dinâmicos Grupos de Recursos de Funcionários (ERGs) são coletivos liderados por funcionários que desempenham um papel fundamental na criação de um ambiente inclusivo e solidário na Databricks. Essas diversas comunidades de funcionários e aliados criam espaço para conexão e celebração e conscientizam sobre questões significativas.Rede Queeries Rede de veteranos Rede de funcionários negros Rede de mulheres Rede LatinX Rede de funcionários asiáticos Nossas experiências"Na Databricks, crio equipes das quais quero fazer parte. Isso significa ter a segurança de ser eu mesma e proporcionar essa mesma zona de conforto a todos ao meu redor. Nosso cuidado mútuo e nosso compromisso com a inclusão têm um grande impacto em toda a nossa comunidade."— Stacy Kerkela, diretora de engenhariaLeia mais"A rede LatinX na Databricks me dá um forte senso de comunidade, uma comunidade aberta. De fato, na Databricks, nossos grupos de recursos de funcionários acolhem e informam todas as pessoas, independentemente de sua origem."— Miguel Peralvo, arquiteto de soluções sêniorLeia mais"Muitas empresas estão focadas em aumentar a diversidade de gênero, mas é ótimo fazer parte de uma empresa que está tomando medidas ativamente para fazer as coisas acontecerem."— Allie Emrich, gerenciamento de programas, produtoLeia maisInclusão na práticaRelatórioParcerias com ColorStack e Rewriting the CodeNossa equipe de recrutamento universitário faz parceria com a ColorStack e Rewriting the Code para ajudar mais mulheres, bem como estudantes negros e LatinX, a seguirem carreira em tecnologia.Leia maisRelatórioPrograma de mentoria Women in TechNa Databricks, reconhecemos a importância de oferecer oportunidades de crescimento profissional e avanço para comunidades historicamente sub-representadas.Leia maisRelatórioPrêmio InHerSight 2021Temos o prazer de ser um dos melhores lugares de trabalho para mulheres em software, de acordo com uma avaliação feita por mulheres. Para saber mais, visite nosso perfil InHerSight.Leia maisVamos construir o futuro dos dados juntosTemos a missão de simplificar e democratizar dados e IA, e precisamos de você para fazer isso acontecer.Explorar oportunidadesProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/legal/databricks-community-edition	Databricks Community Edition \| DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Community EditionCommunity Edition Terms of ServiceWelcome to Databricks Community Edition! We are pleased to provide Databricks Community Edition (the “Community Edition Services”) at no charge to those interested in learning and exploring the use of Databricks’ cloud-based data analytics platform, which enables data analysts and others to easily tap the power of Apache Spark and Databricks’ other proprietary functionality. Your use of the Community Edition Services is governed by these Terms of Service, including the Arbitration Agreement (the “Terms”). If you are using the Community Edition Services on behalf of an organization, you represent and warrant that you are authorized to bind that entity to these Terms, in which case “you” or “your” will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind your entity or do not agree with these Terms, you must not accept these Terms and may not use the Community Edition Services. The effective date of these Terms is the earliest to occur of the date you explicitly accept these Terms, or the date you first access or use the Community Edition Services. BY CLICKING TO ACCEPT THESE TERMS OR USING THE COMMUNITY EDITION SERVICES, YOU ARE REPRESENTING THAT YOU HAVE CAREFULLY READ, UNDERSTOOD AND AGREE TO BE BOUND BY THESE TERMS, INCLUDING WITHOUT LIMITATION THE ACCEPTABLE USE POLICY, THE SECTION TITLED “YOUR DATA AND USE OF COMMUNITY EDITION - RESTRICTIONS APPLY” AND THE SECTION REGARDING MANDATORY, BINDING ARBITRATION OF DISPUTES ENTITLED “DISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVER”.YOUR DATA AND USE OF COMMUNITY EDITION – RESTRICTIONS APPLYThere Are Strict Limits On What Your Data Can Include. In order for us to provide the Community Edition Services to you at no charge, we have implemented certain cost saving elements within the architecture of the Community Edition Services including, among other things, the use of a multi-tenant environment with limited data security protections. In addition, Databricks personnel have generally unrestricted access to your account (“Your Account”) and any data used or exposed to the Community Edition Services for the purposes of monitoring and improving the quality of the service. Therefore, you should have no expectation of privacy regarding the data you submit or otherwise make available in any way to the Community Edition Services (collectively, “Your Data”) or the notebooks you create within or upload to the Community Edition Services (“Your Notebooks”, and collectively with Your Data, “Your Content”) and you must limit Your Content to only that data and other information that you can afford to lose, or have accessed, obtained or disseminated by other parties. Without limiting the foregoing, under no circumstances are you permitted to use with or make available to the Community Edition Services (such data, “Prohibited Data”):any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by this Agreement;any data with respect to which your use and provision to Databricks pursuant to this Agreement would breach any agreement between you and any third party;any data that includes pornography, incitements to violence, terrorism or other wrongdoing, or obscene, illicit or deceptive materials of any kind;any data with respect to which its usage as contemplated herein would violate any applicable local, state, federal or other laws, regulations, orders or rules, including without limitation any privacy laws;any (w) bank, credit card or other financial account numbers or login credentials, (x) social security, tax, driver’s license or other government-issued identification numbers, (y) health information identifiable to a particular individual; or (z) any data that would constitute “special categories of data,” “sensitive personal data,” or any similar concept under applicable law; orany data that is prohibited by the Acceptable Use Policy.You Must Protect Access to Your Account and to Your Content. You are responsible for safeguarding your password and you must make sure no one else has access to it. Additionally, in order to facilitate the sharing and widespread use of the Community Edition Services, we enable you, at your discretion, to share with others access to Your Content. You bear sole responsibility for protecting access to Your Content and for any and all liabilities that may result from the misuse of any sharing privileges granted by you to others. You agree and acknowledge Databricks has a passive role in the transmission, reception and use of Your Content, and Databricks does not take any initiative in the transmission, reception, or use of Your Content. Moreover, as between you and Databricks, you agree and acknowledge that you are solely responsible for your use of Your Content and that Databricks cannot supervise, control, direct, choose, verify, investigate, or evaluate Your Content or your actions with respect to Your Content that you transmit or receive using the Community Edition Services. You acknowledge that we may (but are not obligated to) remove or disable access to any of Your Content, or interrupt any or all services, at any time at our own discretion. You understand and acknowledge that we have the right (but no obligation) to do so if we believe, or are notified, that you have breached any provision of this Agreement (including copyright breach), or if we discontinue or restrict the service that enables you to transmit or receive Your Content. Limits Apply to How You Can Use the Community Edition Services. You agree that your use of the Community Edition Services is subject to the Acceptable Use Policy.DATABRICKS’ LEGAL PROTECTIONS & OTHER PROVISIONSDatabricks Intellectual Property Rights. The Community Edition Services are protected in various ways by copyright, trademark, and other laws of the United States and other countries. These Terms don’t grant you any rights to use of Databricks’ intellectual property, including trademarks, logos and other brand features, except those rights necessary for you to use the Community Edition Services as contemplated under these Terms. Databricks welcomes your feedback but please note that we may use your comments and suggestions freely to improve the Community Edition Services or any of our other products or services, and accordingly you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Community Edition Services or otherwise use any feedback Databricks receives from you. The Community Edition Services are Provided “As Is” With No Warranty. Databricks cannot provide guarantees regarding the Community Edition Services. TO THE FULLEST EXTENT PERMITTED BY LAW, DATABRICKS MAKES NO WARRANTIES, EXPRESS OR IMPLIED, ABOUT THE SERVICES, WHICH ARE PROVIDED “AS IS.” WE DISCLAIM ALL WARRANTIES OF ANY KIND, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NON-INFRINGEMENT, NON-INTERRUPTION, ACCURACY OR DATA SECURITY. Some jurisdictions don’t allow certain of these disclaimers, so they may not apply to you. We Require Your Indemnification. You understand and agree that Databricks bears no liability whatsoever in the event you violate the restrictions and obligations imposed by these Terms regarding your use of the Community Edition Services or for the loss of, or unauthorized access to, Your Data, and that Databricks’ willingness and ability to provide access to you to the Community Edition Services at no charge is contingent upon this understanding, and upon your accepting and adhering to all other provisions of these Terms. You agree to indemnify, defend and hold harmless each of Databricks and its investors, directors, officers, employees, representatives and affiliates from any claims, costs, damages, liabilities or expenses (including reasonable attorneys’ fees) arising out of any third party claim alleging that Your Data or your use of our services infringes the rights of, or has caused harm to, any party, or violates any law or regulation. Limitation on Liability. TO THE FULLEST EXTENT PERMITTED BY LAW, IN NO EVENT WILL DATABRICKS BE LIABLE FOR ANY INDIRECT, SPECIAL, INCIDENTAL, PUNITIVE, EXEMPLARY OR CONSEQUENTIAL DAMAGES OR ANY LOSS OF USE, DATA, BUSINESS OR PROFITS, REGARDLESS OF LEGAL THEORY, REGARDLESS OF WHETHER DATABRICKS HAS BEEN WARNED OF THE POSSIBILITY OF SUCH DAMAGES, AND EVEN IF A REMEDY FAILS OF ITS ESSENTIAL PURPOSE. ADDITIONALLY, DATABRICKS’ AGGREGATE LIABILITY TO YOU FOR ALL CLAIMS RELATING TO THE SERVICES SHALL NOT EXCEED THE GREATER OF THE TOTAL OF ANY AMOUNTS YOU MAY HAVE PAID US IN FEES FOR ANY SERVICE IN THE SIX MONTHS IMMEDIATELY PRIOR TO THE EVENT FIRST GIVING RISE TO ANY SUCH LIABILITY OR $500 (FIVE HUNDRED DOLLARS). THE FOREGOING LIMITATIONS AND EXCLUSIONS SHALL NOT APPLY WITH RESPECT TO ANY LIABILITY ARISING UNDER FRAUD, FRAUDULENT MISREPRESENTATION, GROSS NEGLIGENCE, OR ANY OTHER LIABILITY THAT CANNOT BE LIMITED OR EXCLUDED BY LAW. Some jurisdictions don’t allow the types of limitations in this paragraph, so they may not apply to you. IN THESE JURISDICTIONS, EACH PARTY’S LIABILITY WILL BE FURTHER LIMITED TO THE GREATEST EXTENT PERMITTED BY LAW. You agree that this limitation of liability section is intended to allocate the risks between the parties, and that but for this limitation of liability, Databricks would not make available the Community Edition Services. Entire Agreement; No Third Party Rights. These Terms constitute the entire agreement between you and Databricks concerning the Community Edition Services and these Terms create no third party beneficiary rights. Termination, Modification, Waiver & Assignment. Either of us may suspend or terminate your use of the Community Edition Services or delete Your Account or Your Content at any time and for any reason (including without limitation for any suspected violations of the Acceptable Use Policy); however, obligations of these Terms that by their nature should survive termination shall so survive. In addition, we may revise these Terms from time to time, and will always post the most current version on our website. If we elect to terminate your access to the Community Edition Services or delete Your Account or Your Content, or if a revision of these Terms meaningfully reduces your rights, we will make a reasonable attempt to notify you (by, for example, sending a message to the email address associated with your account or posting for a reasonable time period a message to the login page of the Community Edition Services) unless Databricks deems it necessary to suspend or terminate Your Account without notice. By continuing to use or access the Community Edition Services after the revisions come into effect, you agree to be bound by the revised Terms. Databricks' failure to enforce a provision of these Terms is not a waiver of its right to do so later. If a provision of these Terms is found unenforceable, the remaining provisions of the Terms will remain in full effect and an enforceable term will be substituted reflecting our intent as closely as possible, provided that questions of unenforceability regarding the Arbitration Agreement shall be resolved according to the Severability Section of the Arbitration Agreement. You may not assign or transfer any of your rights under these Terms, and any such attempt will be void. Databricks may assign these Terms and/or its rights under these Terms to any of its affiliates or to any successor in interest.DISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVERInformal Resolution. You agree with us that, if either of us has concerns, we must first work together to resolve any dispute informally without resorting to legal action. You agree to contact us at [email protected] in the event you have a dispute prior to bringing a formal claim against Databricks. If the dispute is not resolved within 30 calendar days from the notice date, either of us may bring a claim subject to the procedures set forth below. You and Databricks agree to the jurisdiction of the Northern District of California to resolve any dispute, claim, or controversy that relates to or arises in connection with these Terms (and any non-contractual disputes/claims relating to or arising in connection with them) and is not subject to mandatory arbitration as set forth below (the “Arbitration Agreement”). Any disputes not subject to mandatory arbitration are subject to the laws of the state of California, without regard to choice or conflicts of law principles. Arbitration Agreement. If you are located within the United States, you and Databricks agree that any dispute, claim, or controversy between you and Databricks arising in connection with or relating in any way to these Terms or to your relationship with Databricks as a user of the Community Edition Services (whether based in contract, tort, statute, fraud, misrepresentation, or any other legal theory, and whether the claims arise during or after the termination of these Terms) will be determined by mandatory binding individual (not class) arbitration. You and Databricks further agree that the arbitrator shall have the exclusive power to rule on his or her own jurisdiction, including any objections with respect to the existence, scope or validity of the Arbitration Agreement or to the arbitrability of any claim or counterclaim. The Arbitration Agreement will survive termination of the Terms. You and Databricks agree that the Federal Arbitration Act applies and governs the interpretation and enforcement of the Arbitration Agreement (despite the choice of law provision above). Exceptions to Arbitration. Notwithstanding the prior clause, you and Databricks both agree that nothing in this Arbitration Agreement will be deemed to waive, preclude, or otherwise limit either of our rights, at any time, to (1) bring an individual action in a U.S. small claims court or (2) bring an individual action seeking only temporary or preliminary individualized injunctive relief in a court of law, pending a final ruling from the arbitrator. In addition, this Arbitration Agreement doesn’t stop you or us from bringing issues to the attention of federal, state, or local agencies. Such agencies can, if the law allows, seek relief against us on your behalf (or vice versa). Prohibition of Class and Representative Actions and Non-Individualized Relief. You and Databricks agree that each of us may bring claims against the other only on an individual basis and not as a plaintiff or class member in any purported class or representative action or proceeding. Unless both you and Databricks agree otherwise, the arbitrator(s) may not consolidate or join more than one person’s or party’s claims and may not otherwise preside over any form of a consolidated, representative or class proceeding. Also, the arbitrator(s) may award relief (including monetary, injunctive and declaratory relief) only in favor of the individual party seeking relief and only to the extent necessary to provide relief necessitated by that party’s individual claim(s). Any relief awarded cannot affect other Databricks customers. Arbitration Procedures. Arbitration is more informal than a lawsuit in court. Arbitration uses a neutral arbitrator or arbitrators instead of a judge or jury, and court review of an arbitration award is very limited. However, the arbitrator(s) can award the same damages and relief on an individual basis that a court can award to an individual. The arbitrator(s) also must follow the terms of these Terms as a court would. The arbitration will be conducted by the American Arbitration Association (referred to as the "AAA") under its rules and procedures, including the AAA's Consumer Arbitration Rules (as applicable), unless you have accepted these Terms as a representative of a business entity, in which case AAA’s Commercial Arbitration Rules shall govern (as applicable), in each case as modified by this Arbitration Agreement. The AAA's rules and forms to commence arbitration are available at www.adr.org. A party who intends to seek arbitration must first send the other party, if to Databricks, by certified mail, a completed Demand for Arbitration. You should send this notice to Databricks at: Databricks, Inc., Attn: Legal Department, Re: Demand for Arbitration, 160 Spear St., Ste. 1300, San Francisco, CA 94105 USA (with a copy to [email protected]). Databricks will send any notice to you to the address we have on file associated with your Databricks account (which may solely be at your account email address); it is your responsibility to keep your address up to date. All information called for in the notice must be provided including a description of the nature and basis of the claims the party is asserting and the relief sought. The arbitration shall be held in the county in which you reside or at another mutually agreed location. If the value of the relief sought is $10,000 or less, you or Databricks may elect to have the arbitration conducted by telephone or based solely on written submissions, which election shall be binding on you and Databricks subject to the discretion of the arbitrator(s) to require an in-person hearing, if the circumstances warrant. In cases where an in-person hearing is held, you and/or Databricks may attend by telephone, unless the arbitrator(s) require otherwise. Any settlement offer made by you or Databricks shall not be disclosed to the arbitrator(s). The arbitrator(s) will decide the substance of all claims in accordance with applicable law, including recognized principles of equity, and will honor all claims of privilege recognized by law. The arbitrator(s) shall not be bound by rulings in prior arbitrations involving different Databricks customers, but is/are bound by rulings in prior arbitrations involving the same Databricks customer to the extent required by applicable law. The award of the arbitrator(s) shall be final and binding, and judgment on the award rendered by the arbitrator(s) may be entered in any court having jurisdiction thereof. Costs of Arbitration. Payment of all filing, administration, and arbitrator fees will be governed by the AAA's rules (either Consumer or Commercial, as applicable), unless otherwise stated in this Arbitration Agreement. If the value of the relief sought by an individual is $10,000 or less, at your request, Databricks will pay all filing, administration, and arbitrator fees associated with the arbitration. Any request for payment of fees by Databricks should be submitted by mail to the AAA along with your Demand for Arbitration and Databricks will make arrangements to pay all necessary fees directly to the AAA. If the value of the relief sought by an individual is more than $10,000 and you are able to demonstrate that the costs of accessing arbitration will be prohibitive as compared to the costs of accessing a court for purposes of pursuing litigation on an individual basis, Databricks will pay as much of the filing, administration, and arbitrator fees as the arbitrator(s) deem necessary to prevent the cost of accessing the arbitration from being prohibitive. In the event the arbitrator(s) determine the claim(s) you assert in the arbitration to be frivolous, you agree to reimburse Databricks for all fees associated with the arbitration paid by Databricks on your behalf that you otherwise would be obligated to pay under the AAA's rules. Severability. With the exception of any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above, if a court decides that any part of this Arbitration Agreement is invalid or unenforceable, the other parts of this Arbitration Agreement shall still apply. If a court decides that any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above is invalid or unenforceable because it would prevent the exercise of a non-waivable right to pursue public injunctive relief, then any dispute regarding the entitlement to such relief (and only that relief) must be severed from arbitration and may be litigated in court; in such case you irrevocably consent to the personal jurisdiction of the state and federal courts in the Northern District of California and such dispute shall be governed by the laws of the state of California, without regard to choice or conflicts of law principles. All other disputes subject to arbitration under the terms of the Arbitration Agreement shall be arbitrated under its terms. Amendments to Arbitration Agreement. Notwithstanding any provision in the Terms to the contrary, you and we agree that if we make any amendment to this Arbitration Agreement (other than an amendment to any notice address or website link provided herein) in the future, that amendment shall not apply to any claim that was filed in a legal proceeding against Databricks prior to the effective date of the amendment. The amendment shall apply to all other disputes or claims governed by this Arbitration Agreement that have arisen or may arise between you and Databricks. We will notify you of amendments to this Arbitration Agreement by posting the amended terms on https://www.databricks.com/ce-termsofuse at least 30 days before the effective date of the amendments and by providing notice through email where possible. If you do not agree to these amended terms, you may close Your Account within the 30-day period and you will not be bound by the amended terms. Last Updated April 9, 2019ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/it/company/partners/technology	Partner tecnologici di Databricks - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio / 8 AM PT Addio, Data Warehouse. Ciao, Lakehouse. Partecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno. Registrati oraSoluzioniSoluzioni per settoreServizi finanziariSanità e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio \| 8am PT Scopri la Lakehouse for Manufacturing Scopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons 26–29 giugno 2023 Partecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perché Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPartner tecnologici di DatabricksEntra in contatto con i Databricks Technology Partner per integrare funzionalità di acquisizione dati, business intelligence e governance con Databricks Lakehouse Platform.“Con Databricks e Fivetran, in futuro saremo in grado di migliorare notevolmente le informazioni di marketing. Dal punto di vista tecnico, i due strumenti interagiscono in modo armonico e l'integrazione è molto stretta”.— Jan-Niklas Mühlenbrock, Team Lead, Business Intelligence & ERP di Paul HewittI Databricks Technology Partner integrano le loro soluzioni con Databricks per offrire funzionalità complementari per ETL, acquisizione di dati, business intelligence, machine learning e governance.Queste integrazioni consentono ai clienti di sfruttare l'affidabilità e la scalabilità della Databricks Lakehouse Platform per fare innovazione più velocemente, ottenendo al tempo stesso informazioni preziose dai dati.Partner ConnectRiunisci tutti gli strumenti di gestione e analisi dei dati e di AI su un'unica piattaforma aperta. Con Partner Connect, Databricks offre un modo semplice e veloce per collegare gli strumenti esistenti al lakehouse utilizzando integrazioni validate, e aiuta a individuare e provare nuove soluzioni.Diventa partnerMaggiori informazioniLoading...ProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiPosizioni aperte in DatabricksMondoEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Informativa sulla privacy\|Condizioni d'uso\|Le vostre scelte sulla privacy\|I vostri diritti di privacy in California
https://www.databricks.com/glossary/spark-api	What is a Spark API?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark APIAll>Spark APITry Databricks for freeGet StartedIf you are working with Spark, you will come across the three APIs: DataFrames, Datasets, and RDDsWhat are Resilient Distributed Datasets?RDD or Resilient Distributed Datasets, is a collection of records with distributed computing, which are fault tolerant, immutable in nature. They can be operated on in parallel with low-level APIs, while their lazy feature makes the spark operation to work at an improved speed. RDDs support two types of operations:Transformations - lazy operations that return another RDD, this RDD doesn’t compute unless action is performed on it. Some examples of transformations are map(), flatmap(), filter() Actions - operations that trigger computation and return values. Some examples of actions are count, top(), savetofile() Disadvantages of RDDsIf you choose to work with RDD you will have to optimize each and every RDD. In addition, unlike Datasets and DataFrames, RDDs don’t infer the schema of the data ingested therefore you will have to specify it.What are DataFrames?DataFrames is a distributed collection of rows under named columns. In simple terms, it looks like an Excel sheet with Column headers, or you can think of it as the equivalent to a table in a relational database or a DataFrame in R or Python. It has three main common characteristics with RDD:Immutable in nature: You will be able to create a DataFrame but you will not be able to change it. A DataFrame just like an RDD can be transformedLazy Evaluations: a task is not executed until an action is performed.Distributed: DataFrames just like RDDs are both distributed in nature.Ways to Create a DataFrameIn Spark DataFrames can be created in several ways:Using different data formats. Such as loading the data from JSON, CSV, RDBMS, XML or ParquetLoading the data from an already existing RDD.Programmatically specifying schemaDisadvantages of DataFramesThe main drawback of DataFrame API is that it does not support compile time safely, as a result, the user is limited in case the structure of the data is not known.What are Datasets?A Dataset is a strongly-typed, immutable collection of objects that are mapped to a relational schema. A Dataset can be created using JVM objects and manipulated using complex functional transformations. Datasets can be created in two ways:DynamicallyReading from a JSON file using SparkSession.Disadvantages of DataSetsThe main disadvantage of datasets is that they require typecasting into strings.Additional Resources8 Steps for a Developer to Learn Apache Spark with Delta Lake eBookThe Data Engineer's Guide to Apache Spark and Delta Lake eBookComparing Apache Spark and DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/jp/company/partners	パートナー \| DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT さようなら、データウェアハウス。こんにちは、レイクハウス。データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 \|午前8時(太平洋標準時) 製造業のためのレイクハウスを発見するコーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOWパートナーデータブリックスは、データ、分析、AI に関わるソリューションおよびサービスを提供する世界中の 1200+ 社以上のパートナーと連携しています。このパートナーシップを通じて、レイクハウスプラットフォームを基盤とするデータと AI のワークロードの統合、より有用な知見の抽出を可能にしています。「Databricksはデータ量を、Tableauは高速なビジュアライゼーションを提供します。これらのソリューションは、当社のプラットフォームの中核で完璧に連携し、最先端の自律走行機能を提供するために必要なパフォーマンスをお客様に提供します。"— Patrick McAuliffe, Lead Engineer, Inciteクラウドパートナーデータブリックスは、 AWS、Microsoft Azure、Google Cloud、Alibaba Cloud と連携し、各プロバイダのインフラ、データ、AI サービスと緊密に統合します。技術パートナー技術パートナーは、ソリューションをデータブリックスと統合し、ETL、データの取り込み、BI、機械学習、ガバナンスのためのケイパビリティを高めます。コンサルティングパートナーSI／コンサルティングパートナーは、それぞれ独自のポジショニングで、お客様におけるデータ、分析、AI に対する取り組みの戦略策定、展開、スケーリングを支援しています。パートナーになるデータブリックスは、パートナー企業との連携を通じて革新的なソリューションを構築し、お客様に提供しています。データブリックスのパートナープログラムに参加することにより、パートナー向けのツールやトレーニング、ソリューションアクセラレータ、Go-to-Market プログラムにアクセスできます。詳しく見る製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.プライバシー通知\|利用規約\|プライバシー設定\|カリフォルニア州のプライバシー権利
https://www.databricks.com/dataaisummit/speaker/satya-nadella/#	Satya Nadella - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSatya NadellaChairman and CEO at Microsoft, Live Virtual GuestBack to speakersSatya Nadella is Chairman and Chief Executive Officer of Microsoft. Before being named CEO in February 2014, Nadella held leadership roles in both enterprise and consumer businesses across the company. Joining Microsoft in 1992, he quickly became known as a leader who could span a breadth of technologies and businesses to transform some of Microsoft’s biggest product offerings. Most recently, Nadella was executive vice president of Microsoft’s Cloud and Enterprise group. In this role he led the transformation to the cloud infrastructure and services business, which outperformed the market and took share from competition. Previously, Nadella led R&D for the Online Services Division and was vice president of the Microsoft Business Division. Before joining Microsoft, Nadella was a member of the technology staff at Sun Microsystems. Originally from Hyderabad, India, Nadella lives in Bellevue, Washington, with his family. He earned a bachelor’s degree in electrical engineering from Mangalore University, a master’s degree in computer science from the University of Wisconsin – Milwaukee and a master’s degree in business administration from the University of Chicago. Nadella serves on the board of trustees to his alma mater the University of Chicago, as well as the Starbucks board of directors.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/p/ebook/learn-apache-spark-with-delta-lake	Learn Apache Spark™ with Delta Lake - DatabrickseBookUnlock the potential of your dataLearn how Apache Spark™ and Delta Lake unify all your data — big data and business data — on one platform for BI and ML.Apache Spark 3.x is a monumental shift in ease of use, higher performance and smarter unification of APIs across Spark components. And for the data being processed, Delta Lake brings data reliability and performance to data lakes, with capabilities like ACID transactions, schema enforcement, DML commands and time travel.In this eBook, we offer a step-by-step guide to technical content and related assets that will lead you to learn Apache Spark and Delta Lake. Whether you’re just getting started or you’re already an accomplished developer, explore the benefits of these open source projects.Here are the 8 steps we’ll cover:Why Apache Spark and Delta LakeApache Spark concepts, key terms and keywordsAdvanced Apache Spark internals and coreDataFrames, data sets and Spark SQL essentialsGraph processing with GraphFramesContinuous applications with structured streamingMachine learning for humansReliable data lakes and data pipelinesGet the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/it/solutions/industries/media-and-entertainment	Soluzioni per media e intrattenimento - Databricks Lakehouse - DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio / 8 AM PT Addio, Data Warehouse. Ciao, Lakehouse. Partecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno. Registrati oraSoluzioniSoluzioni per settoreServizi finanziariSanità e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio \| 8am PT Scopri la Lakehouse for Manufacturing Scopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons 26–29 giugno 2023 Partecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perché Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWDatabricks per media e intrattenimentoProiettare il settore dei media in un futuro guidato da dati, analisi e AICominciaProgramma una demoQuattro sfide per la gestione dei dati nel settore di media e intrattenimentoCreare un profilo unificato del pubblico Dati acquisiti, conservati e gestiti con diversi sistemi impediscono alle organizzazioni di avere una visione completa dei dati del pubblico e degli inserzionisti.Offrire un'esperienza utente eccezionale I consumatori si aspettano esperienze 1:1 personalizzate e fluide in qualsiasi momento su tutti i loro dispositivi. La sfida è offrire queste esperienze in tempo reale e su larga scala.Massimizzare il patrimonio di dati I data warehouse esistenti non sono in grado di gestire dati non strutturati come video, immagini e file audio, impedendo alle organizzazioni di sfruttare pienamente il potenziale delle loro risorse più preziose.Passare dall'aggregazione alle analisi avanzate Casi complessi di utilizzo dell'AI per il ciclo di vita della pubblicità e dei consumatori comportano attualmente costi elevati per l'acquisizione e l'armonizzazione di set massicci di dati.Scopri il Data Lakehouse: il meglio di due mondi su un'unica piattaformaUn data lakehouse unisce il meglio dei data warehouse e dei data lake in un'unica piattaforma semplice per gestire tutti i casi di utilizzo di dati, analisi e AI. È costruito su una piattaforma aperta e affidabile che gestisce in maniera efficiente tutti i tipi di dati e applica un unico approccio comune alla sicurezza e alla governance, per tutti i dati e le piattaforme cloud.Maggiori informazioniIl lakehouse in azioneScopri come Databricks Lakehouse supporta il tuo settore specificoTecnologie per pubblicità e marketingGestisci i margini e le attività operative con un approccio rigoroso incentrato sui dati, migliora le prestazioni dei media e ottimizza la creatività per snellire il lavoro dei team.Maggiori informazioniBroadcasting e streamingCrea esperienze personalizzate 1:1 su larga scala, migliora i risultati e l'ottimizzazione della pubblicità e genera più valore dall'intero portafoglio di contenuti.Maggiori informazioniVideogameSfrutta dati e AI per migliorare la progettazione di giochi, aumentare l'acquisizione e il coinvolgimento dei giocatori e incrementare la monetizzazione e la fidelizzazione dei giocatori.Maggiori informazioniPerché Databricks per media e intrattenimentoTutti i dati, le analisi e l'AI su un'unica piattaforma Estrapola tutto il valore dai tuoi dati per ottenere risultati eccezionali in termini di coinvolgimento del pubblico, monetizzazione e ottimizzazione della pubblicità.Ottimizzato per il tempo reale Scopri informazioni fruibili, promuovi la personalizzazione 1:1 e migliora l'esperienza del tuo pubblico mettendo al centro il machine learning.Risultati in tempi più rapidi Sfrutta una serie di acceleratori che semplificano l'acquisizione di dati dei consumatori (ad esempio il flusso di clic per misurare il coinvolgimento) e la creazione di casi d'uso come motori di raccomandazioni e attribuzione multitouch.Affidabilità e prestazioni ai massimi livelli Databricks Lakehouse offre scalabilità, velocità e risparmi senza precedenti. Non c'è da meravigliarsi che il miglior data warehouse sia un lakehouse.Trasformare il settore di media e intrattenimento con il lakehouse “Con Databricks Lakehouse Platform su AWS, Warner Bros. Discovery è pronta per affrontare il futuro della scoperta di contenuti e delle esperienze per il pubblico. Sfruttando i dati per prevedere meglio il comportamento del consumatore e fornire consigli mirati sui contenuti in tempo reale, riusciamo a personalizzare l'esperienza dello spettatore e ad aumentare il coinvolgimento complessivo dei nostri clienti”.— Martin Ma, GVP, Engineering di Warner Bros. DiscoveryApprofondimenti dei dirigenti su dati, analisi e AIScopri che cosa stanno facendo altri dirigenti nel settore di media e intrattenimento per potenziare la loro strategia di gestione dei datiMaggiori informazioniChe cosa si può fare con il lakehouse? Accelerare il conseguimento di risultati per pubblico e inserzionisti su una piattaforma collaborativa aperta per dati, analisi e AIVista a 360° del pubblico Raccogli tutti i dati strutturati e non strutturati (flusso di clic, demografici, sociali) su un'unica piattaforma per analisi e AI. Grazie a una visione a 360 gradi del percorso del consumatore, le organizzazioni possono individuare le preferenze di contenuti per offrire esperienze più personalizzate, proporre annunci pubblicitari più mirati e aumentare il coinvolgimento.Riduzione delle disdette e incremento del ricavo medio per unità (ARPU) Grazie a una piattaforma agile in cloud, le organizzazioni possono elaborare in modo veloce e affidabile enormi quantità di dati e inviarli a sistemi a valle per offrire un'esperienza personalizzata su qualsiasi canale in qualsiasi momento. I consumatori si aspettano sempre di più di ricevere consigli in tempo reale e le società di media competono per attirare l'attenzione del pubblico: in questo contesto, la personalizzazione in tempo reale diventa un requisito essenziale per molte organizzazioni.Generare ricavi da una libreria di contenuti Le società di media basano la loro attività su dati non strutturati come video, immagini e file audio, pertanto la capacità di analizzare dati non strutturati è fondamentale per un'efficace gestione del patrimonio di media. La soluzione Lakehouse per il settore media e intrattenimento consente agli addetti al marketing di sfruttare i contenuti archiviati per le campagne, ai team di produzione di cercare contenuti esistenti da inserire in nuove produzioni e ai team di vendita di trovare proprietà intellettuale da vendere ad altre società.Sfrutta modelli precostruiti per ML/AI. La tecnologia ML al centro del business Sfruttando la potenza del machine learning si possono capire meglio le esigenze di consumatori, dipendenti e inserzionisti. Quando tutti i dati sono centralizzati e strettamente collegati da una suite completa di strumenti collaborativi per analisi e machine learning, i team di gestione dei dati possono lavorare insieme per costruire potenti modelli predittivi che favoriscono l'innovazione negli ambiti della personalizzazione, della monetizzazione dei contenuti e dei risultati per gli inserzionisti.Scarica l'eBookPartner e soluzioni Comincia a operare con una gamma di soluzioni di gestione e analisi dei dati e di template specifici per il settore dei media e dell'intrattenimento Visita il nostro Portale dei PartnerAttribuzione multitouchMisura l'efficacia degli annunci pubblicitari e ottimizza le spese di marketing con una migliore attribuzione dei canaliCominciaTossicità di giocatori/utentiCrea comunità di utenti più sane rilevando in tempo reale linguaggi e comportamenti tossiciCominciaAnalisi della sopravvivenza/LTVIndividua i consumatori a rischio di disdetta e i fattori chiave per prolungare il ciclo di vita di ogni consumatoreCominciaPropensione all'abbandonoGestisci efficacemente la ritenzione dei clienti, analizza il ciclo di vita e riduci il tasso di abbandono (disdette)CominciaSegmentazione comportamentaleCrea una segmentazione più avanzata dei clienti per migliorare le previsioni di acquisto in base ai comportamentiCominciaPrevisioni di vendita e attribuzioneMigliora i risultati degli annunci pubblicitari concentrando l'attenzione sui canali che offrono i risultati miglioriCominciaRaccomandatiAumenta le conversioni e il coinvolgimento con consigli personalizzati su tutti i canaliCominciaComputer vision/LabelboxAnnota immagini e video per contestualizzare gli annunci pubblicitari nel lakehouse ProssimamenteQualità di esperienza videoAnalizza i dati in batch e in streaming per garantire un'esperienza di qualità nella fruizione di contenuti in streamingCominciaOfferte in tempo reale (RTB)Scopri come prevedere la visibilità degli annunci pubblicitari in tempo reale per migliorare la strategia RTBCominciaVedi tutte le soluzioniLakehouse for Media & Entertainment in azioneRisorse Tutte le risorse di cui hai bisogno in un unico posto. Esplora la libreria di risorse per trovare e-book e video su dati, analisi e AI per il settore media e intrattenimento Esplora risorseeBookSCARICAWebinarMaggiori informazioniBlogMaggiori informazioniPronto per cominciare?Vorremmo conoscere i tuoi obiettivi aziendali e come il nostro team di servizi potrebbe aiutarti a realizzarli.Prova Databricks gratisProgramma una demoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiPosizioni aperte in DatabricksMondoEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/spark/about	About Spark – DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWApache Spark™Apache Spark is a lightning-fast unified analytics engine for big data and machine learning. It was originally developed at UC Berkeley in 2009.The largest open source project in data processing.Since its release, Apache Spark, the unified analytics engine, has seen rapid adoption by enterprises across a wide range of industries. Internet powerhouses such as Netflix, Yahoo, and eBay have deployed Spark at massive scale, collectively processing multiple petabytes of data on clusters of over 8,000 nodes. It has quickly become the largest open source community in big data, with over 1000 contributors from 250+ organizations.The team that started the Spark research project at UC Berkeley founded Databricks in 2013.Apache Spark is 100% open source, hosted at the vendor-independent Apache Software Foundation. At Databricks, we are fully committed to maintaining this open development model. Together with the Spark community, Databricks continues to contribute heavily to the Apache Spark project, through both development and community evangelism.Watch the videoWhat is Apache Spark - Benefits of Apache SparkSpeed Engineered from the bottom-up for performance, Spark can be 100x faster than Hadoop for large scale data processing by exploiting in memory computing and other optimizations. Spark is also fast when data is stored on disk, and currently holds the world record for large-scale on-disk sorting. Ease of Use Spark has easy-to-use APIs for operating on large datasets. This includes a collection of over 100 operators for transforming data and familiar data frame APIs for manipulating semi-structured data.A Unified Engine Spark comes packaged with higher-level libraries, including support for SQL queries, streaming data, machine learning and graph processing. These standard libraries increase developer productivity and can be seamlessly combined to create complex workflows.Try Apache Spark on the Databricks cloud for freeThe Databricks Unified Analytics Platform offers 5x performance over open source Spark, collaborative notebooks, integrated workflows, and enterprise security — all in a fully managed cloud platform.Try DatabricksThe open source Apache Spark project can be downloaded hereProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/de/product/unity-catalog	Unity Catalog \| DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse. Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt. Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai \| 8 Uhr PT Entdecken Sie das Lakehouse für die Fertigung Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023 Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWUnity CatalogVereinheitlichung von Governance und Teilen für Daten, Analytics und KI Erste SchritteDemo ansehen WEBINAR • Goodbye, Data Warehouse. Hello, Lakehouse. Attend on May 18 and get a $100 credit toward a Databricks certification course Register nowUnity Catalog ist eine einheitliche Governance-Lösung für alle Daten- und KI-Assets einschließlich Dateien, Tabellen und Machine-Learning-Modellen in Ihrem Lakehouse in jeder Cloud.Zentralisierte Governance für Daten und KIMit einem gemeinsamen Governance-Modell, das auf ANSI SQL basiert, können Sie Dateien, Tabellen, Dashboards und ML-Modelle in jeder Cloud zentral verwalten.Integrierte Datensuche und -erkennungFinden, verstehen und referenzieren Sie schnell Daten aus Ihrem gesamten Datenbestand und steigern Sie so die Produktivität.Leistung und SkalierbarkeitProfitieren Sie von einer verbesserten Abfrageleistung mit Metadaten mit geringer Latenz, die die Tabellen bereitstellen und automatisch abstimmen.Automatisierte Herkunftsbestimmung für alle WorkloadsErstellen Sie eine einheitliche, transparente Ansicht Ihres gesamten Datenökosystems mit automatisierter und granularer Herkunftsbestimmung für alle Workloads in SQL, R, Python, Scala und über alle Asset-Typen hinweg – Tabellen, Notebooks, Workflows und Dashboards.In vorhandene Tools integrierbarMachen Sie Ihre Daten- und KI-Governance zukunftssicher mit der Flexibilität, Ihre vorhandenen Datenkataloge und Governance-Lösungen zu nutzen.Wie es funktioniertAlle Daten-Assets zentral verwalten und kontrollierenMit einem gängigen Governance-Modell basierend auf offenem Standard ANSI SQL vereinfachen Sie die Governance für Dateien, Tabellen, Dashboards und ML-Modelle in jeder Cloud. Definieren Sie Zugriffsrichtlinien einmal auf Kontoebene und setzen Sie sie für alle Workloads und Arbeitsbereiche durch. Unity Catalog bietet außerdem zentralisiertes, fein abgestimmtes Auditing, indem er ein Auditprotokoll der für die Daten durchgeführten Aktionen erfasst und Ihnen hilft, Ihre Compliance- und Audit-Anforderungen zu erfüllen. Feingeprüfte Zugriffskontrollen verwaltenVerwenden Sie Standard-SQL-Funktionen, um Zeilenfilter und Spaltenmasken zu definieren, die detaillierte Zugriffskontrollen für Zeilen und Spalten ermöglichen. Da Databricks weiterhin Funktionen zur Verbesserung der Skalierbarkeit und Integration ausbaut, werden Sie mit den kommenden attributbasierten Zugriffssteuerungen Zugriffsrichtlinien basierend auf benutzerdefinierten Tags (Attributen) definieren können.Einheitliches und sicheres DatensucherlebnisFinden, verstehen und referenzieren Sie schnell relevante Daten aus Ihrem gesamten Datenbestand mit einer einheitlichen Datensuche für Datenanalysten, Data Engineers und Data Scientists. Die Datensuche in Unity Catalog ist standardmäßig sicher, indem sie die Suchergebnisse auf der Grundlage der Zugriffsrechte der Benutzer einschränkt und eine zusätzliche Sicherheitsebene aus Datenschutzgründen hinzufügt.Verbesserte Abfrageleistung in jeder GrößenordnungUnity Catalog bietet eine verbesserte Abfrageleistung mit Metadaten mit geringer Latenz und automatischer Tabellenabstimmung, was zu einer schnelleren Ausführung von Abfragen in jeder Größenordnung führt. Asynchrone automatische Datenverdichtung optimiert Dateigrößen und reduziert die E/A-Latenz (Eingang/Ausgang) automatisch im Hintergrund.Automatisierte Datenherkunftsbestimmung in EchtzeitVerschaffen Sie sich einen umfassenden Überblick über den Datenfluss in Ihrem Lakehouse mit automatisierter und Echtzeit-Datenherkunftsbestimmung über alle Workloads in SQL, Python, Scala und R hinweg. Führen Sie schnell Datenqualitätsprüfungen durch, führen Sie eine umfassende Analyse der Auswirkungen von Datenänderungen durch und beheben Sie Fehler in Ihren Datenpipelines. Profitieren Sie von Herkunftsbestimmung über Tabellen, Spalten, Notebooks, Workflows und Dashboards hinweg. Herkunftsdiagramme in Unity Catalog sind berechtigungsbewusst und beschränken den Zugriff basierend auf den Zugriffsberechtigungen der Benutzer. Die Herkunft kann auch über die REST-API abgerufen werden, um die Integration mit anderen Katalogen zu unterstützen.Sicherer Datenaustausch zwischen OrganisationenUnity Catalog unterstützt nativ Delta Sharing, das weltweit erste offene Protokoll für die sichere Datenfreigabe, mit dem Sie vorhandene Daten problemlos in Delta Lake- und Apache Parquet-Formaten für jede beliebige Computerplattform freigeben können. Verbraucher müssen sich nicht auf der Databricks-Plattform, in derselben Cloud oder überhaupt in einer Cloud befinden. Sie können Live-Daten freigeben, ohne sie zu replizieren oder auf ein anderes System zu kopieren. Native Integrationen mit Power BI, Tableau, Spark, Pandas und Java ermöglichen es Empfängern, freigegebene Daten direkt aus den Tools ihrer Wahl zu nutzen. Verwalten, kontrollieren, prüfen und verfolgen Sie die Nutzung der freigegebenen Daten zentral auf einer Plattform.Nahtlose Integration in Ihre vorhandenen ToolsUnity Catalog arbeitet mit Ihren vorhandenen Datenkatalogen, Datenspeichersystemen und Governance-Lösungen zusammen, sodass Sie Ihre vorhandenen Investitionen nutzen und ein zukunftssicheres Governance-Modell ohne teure Migrationskosten aufbauen können.Daten- und Cloud-SpeicherData Governance- und KatalogpartnerKundschaft"Unity Catalog half uns, das Datenmanagement und die Zugriffskontrollen im gesamten Unternehmen zu vereinfachen. Das Compass-Datenteam hat mehr als 100 Datenquellen sicher eingebunden, alle Arbeitsbereiche zu Unity Catalog migriert und eine Goldschicht geschaffen, auf die wichtige Stakeholder zugreifen können, um Einblicke in Bereiche wie Kunden, Produkte, Nutzung, Umsatz und mehr zu erhalten – und so eine Single Source of Truth mit vollständiger Zugriffskontrolle im gesamten Unternehmen.“— Rajesh Nagpal, Leitender Direktor für Datentechnik„Unity Catalog hat unsere Implementierung der rollenbasierten Zugriffskontrolle erheblich vereinfacht, sodass wir Daten auf Katalog-, Datenbank-, Tabellen- und Spaltenebene sichern konnten. Wir stellen den entsprechenden Zugriff nahtlos für alle Benutzer bereit und können den Datenzugriff zuverlässig verwalten und sichern, um unsere strengen Compliance- und Datenschutzrichtlinien zu erfüllen.“– Chris Locklin, Engineering Manager of Data Platforms, Grammarly„Unity Catalog hat es Milliman ermöglicht, seine umfangreichen Datenbestände direkt an seine Benutzer zu binden, was das Zugriffsmanagement vereinfacht und die Speicherkomplexität reduziert. Unity Catalog ermöglicht es Milliman, strenge Gesundheitsversorgungsstandards zu erfüllen, kollaborative Datenexploration zu ermöglichen und die Speicherkomplexität zu reduzieren. Mit Unity Catalog können wir schnell skalieren, um die Bedürfnisse unserer Kunden zu erfüllen.“– Dan McCurley, Cloud Solutions Architect, Milliman„Unity Catalog ermöglicht es uns, eine Plattform der nächsten Generation aufzubauen, die das volle Potenzial von softwaredefinierten Fahrzeugen erschließt, die sich weiterentwickeln und verbessern, während sie Kilometer zurücklegen – das Fahrerlebnis für Kunden verbessern und die Umweltvorteile des elektrifizierten Transports maximieren. Wir haben jetzt einen zentralisierten Datenkatalog und eine Zugriffsverwaltung für verschiedene Teams und Arbeitsbereiche, was beispiellose Möglichkeiten für Zusammenarbeit und Innovation eröffnet hat.“— Venkat Sivasubramanian, Leitender Direktor, Big Data„Unity Catalog hat für uns das Spiel verändert. Unsere Analysten können in Databricks Workspaces in Echtzeit auf externe AWS-Tabellen zugreifen und sie mit Delta Lake-Tabellen verbinden. Es bietet uns die Leistungsvorteile von Databricks SQL, ohne Glue-Tabellen zu migrieren. Mit Unity Catalog können verschiedene Teams zusammenarbeiten, ohne die Daten von einem Ort an einen anderen zu verschieben.“– Rajat Gupta, Engineering Manager, Warner Bros. DiscoveryRessourcenKeynote und Webinar[Keynote]Data Governance and sharing on the lakehouse beim Data + AI Summit 2022[On-Demand-Webinar]So vereinfachen Sie die Daten- und KI-GovernanceeBooks und Blogs[eBook] Daten, Analysen und KI-GovernanceAnkündigung der allgemeinen Verfügbarkeit der Datenherkunft im Unity-KatalogAnkündigung der Verfügbarkeit von Data Lineage mit Unity CatalogEinführung des Databricks Unity-Katalogs: Feinkörnige Governance für Daten und KI im LakehouseDokumentationAWS-DokumentationAzure-DokumentationMöchten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter „Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/dataaisummit/speaker/mahesh-prakriya/#	Mahesh Prakriya - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMahesh PrakriyaDirector in Intelligence Platform at MicrosoftBack to speakersMahesh Prakriya is a Director in Azure Data focused on ISVs and partnerships. Over 20+ years at Microsoft and industry, Mahesh shipped some of the key data and app platforms customer depend on including Power BI, Data Integration components, SQL Server, .NET Framework, Windows & Bing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/todd-greenstein/#	Todd Greenstein - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTodd GreensteinProduct Manager at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/rakesh-singh	Rakesh Singh - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRakesh SinghLead Architect at ABN AMRO Bank N.VBack to speakersLead Solution Architect and responsible for designing a future-proof data platform for ABN AMRO BankLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/deylo-woo	Deylo Woo - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeylo WooData Engineer Architect at Providence Health ServicesBack to speakersDeylo Woo attended University of Alaska Anchorage (Computer Science) and is an experienced IT professional with 22 years of experience and 12 years with Providence Health Services. He specializes in Software and Data Engineering, and has worked with various technologies such as Java, .Net (C#), Javascript, Python, SQL, Data Warehouses, ETL development, and cloud architectures. Deylo is originally from Brazil but grew up in the US (Alaska) where his favorite past time is camping and fishing.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/ruifeng-zheng	Ruifeng Zheng - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRuifeng ZhengSenior Software Engineer at DatabricksBack to speakersRuifeng is currently a Databricks software engineer, Apache Spark committer, working on several different modules in Apache Spark including Spark Connect, Pandas API on Spark, PySpark, MLlib, Spark SQL, SparkR, etc. Prior to Databricks, he worked on applied machine learning for 10+ years. He holds a Master degree in Electronics Engineering from Peking University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/risha-ravindranath/#	Risha Ravindranath - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRisha RavindranathSr Manager, Data Governance at Comcast AdvertisingBack to speakersRisha Ravindranath brings 10+ years of experience in Data Governance and Business Analysis. She is a highly involved business analyst who expertly brings solutions together to drive end-to-end data governance programs integrated with technical solutions. Risha currently is a Senior Manager of Data Governance at Comcast Effectv.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/p/ebook/the-big-book-of-mlops?itm_data=home-promocard3-bigbookmlops	The Big Book of MLOps \| DatabrickseBookA new data-centric approach to building robust MLOps practicesDiscover the fastest path to get machine learning models to production. The Big Book of MLOps will show you how data engineers, data scientists, and machine learning engineers can build and collaborate on a common platform, using powerful and open frameworks such as Delta Lake for data pipelines, MLflow for model management and Databricks Workflows for automation.In this eBook, you’ll learn:The essential components of an MLOps reference architectureThe key stakeholders to involve as you build and deploy machine learning applicationsHow to leverage the same platform for data and models and get to production fasterHow to monitor data and models through the complete ML lifecycle with end-to-end lineageBest practices to guide your MLOps planning and decision-makingDownload your copyProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/solutions/accelerators/digital-pathology	Digital Pathology Image Analysis \| DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorDigital Pathology Image AnalysisPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedImprove the efficiency of diagnostic teams with deep learningHelp augment diagnostic workflows with this Databricks Solution Accelerator for pathology image analysis. Now you can rapidly process thousands of whole slide images in minutes and use machine learning to automate the detection of metastasis. Findings are visualized with a metastasis probability heat map that can be shared with diagnostic teams.Accelerate image analysis at scaleAutomate the detection of cancer metastasisEnable clinical reproducibilityDownload notebookResourcesSelf guided tourLearn moreWebinarLearn moreBlogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/blog/2021/12/15/announcing-general-availability-of-databricks-sql.html	Announcing General Availability of Databricks SQL - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29 Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorAnnouncing General Availability of Databricks SQLby Bilal Aslam, Can Efeoglu, Erika Ehrli, Shant Hovsepian, Paul Leventis, Cyrielle Simeone and Reynold XinDecember 15, 2021 in Platform BlogShare this postToday, we are thrilled to announce that Databricks SQL is Generally Available (GA)! This follows our earlier announcements about Databricks SQL’s world record-setting performance for data warehousing workloads, and adoption of standard ANSI SQL. With GA, you can expect the highest level of stability, support and enterprise-readiness from Databricks for mission-critical workloads on the Databricks Lakehouse Platform. In this blog post, we explore how Databricks SQL is powering a new generation of analytics and data applications, running directly on the data lake, at the world’s leading companies.Customers win with the open lakehouseHistorically, data teams had to resort to a bifurcated architecture to run traditional BI and analytics workloads, copying subsets of the data already stored in their data lake to a legacy data warehouse. Unfortunately, this led to the lock-in, high costs and complex governance inherent in proprietary architectures.Our customers asked us to simplify their data architecture. We introduced Databricks SQL to provide data warehousing capabilities and first class support for SQL on the Databricks Lakehouse Platform. Using open standards, Databricks SQL provides up to 12x better price/performance for data warehousing and analytics workloads on existing data lakes. And it works seamlessly with popular tools like Tableau, PowerBI, Looker, and dbt without sacrificing concurrency, latency and scale, all the while maintaining a single source of truth for your data.Databricks SQL is already powering production use cases at leading companies around the globe. From startups to enterprises, over 1,000 companies are using Databricks SQL to power the next generation of self-served analytics and data applications:Atlassian is building on the Lakehouse Platform one of the most ambitious data applications on the planet, providing nearly 190K external users with the ability to generate insights and analytics on the freshest data. Databricks SQL is also enabling data democratization internally across over 3K users, and more BI workloads are moving to Databricks SQL with PowerBI.Punchh has accelerated ETL pipelines, democratized data and analytics, and improved BI and reporting—increasing customer retention and loyalty. Databricks SQL allows Punchh’s data team to query their data directly within Databricks and then share insights through rich visualizations and fast reporting via Tableau.SEGA Europe has moved away from a costly data warehouse-centric architecture to the Databricks Lakehouse Platform. And in doing so, successfully unified massive amounts of structured and unstructured data. This enables their data teams to derive insights needed to deliver personalized experiences to 30 million gamers across the globe. SEGA Europe’s existing BI tools, Tableau and PowerBI, work seamlessly with Databricks SQL.Powering modern analytics on the lakehouseDatabricks SQL offers all the capabilities you need to run data warehousing and analytics workloads on the Databricks Lakehouse Platform:Instant, elastic SQL-optimized compute for low-latency, high-concurrency queries that are typical in analytics workloads. Compute is separated from storage so you can scale with confidence.Integration with your existing tools such as Tableau, PowerBI, dbt and Fivetran, so you can get value from your data without having to learn new solutions.Simplified administration and data governance, so you can quickly and confidently enable self-serve analytics.A first-class, built-in analytics experience with a SQL query editor, visualizations and interactive dashboards. Analysts can go from zero-to-aha! in moments.We can’t wait to see what you buildWatch the demo below to discover the ease of use of Databricks SQL for analysts and administrators alike:To play this video, click here and accept cookiesIf you already are a Databricks customer, follow the guide to get started (AWS \| Azure). Read the release notes to learn more about what's included in this GA release. If you are not an existing Databricks customer, sign up for a free trial with a Premium or Enterprise workspace.Watch Delivering Analytics on the Lakehouse with Reynold Xin to learn more, and don’t miss our free virtual training on January 13, 2022 to dive in!Try Databricks for freeGet StartedRelated postsAnnouncing General Availability of Databricks SQLDecember 15, 2021 by Bilal Aslam, Can Efeoglu, Erika Ehrli, Shant Hovsepian, Paul Leventis, Cyrielle Simeone and Reynold Xin in Platform Blog Today, we are thrilled to announce that Databricks SQL is Generally Available (GA)! This follows our earlier announcements about Databricks SQL’s world record-setting p... See all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice\|Terms of Use\|Your Privacy Choices\|Your California Privacy Rights
https://www.databricks.com/dataaisummit/speaker/shawn-gilleran	Shawn Gilleran - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShawn GilleranPrincipal Cloud Solutions Lead at LiveRampBack to speakersShawn Gilleran leads cloud solutions at LiveRamp, helping clients leverage identity for safe and effective data use in the cloud. With over 30 years in IT, he's an expert in managed infrastructure, specializing in identity resolution for marketing, compliance, and modeling. Prior to LiveRamp, he spent 25 years at Acxiom and founded Vortex, a company focused on data monetization. Shawn holds a BS in computer science and is a patent holder for marketing technologies. He resides in Little Rock, AR.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/explore/financial-services-resources/video-lakehouse-for-financial-services	Video: Lakehouse for Financial Services Video is muted due to browser restrictions. Adjust the volume on the video player to unmute. Selected language is not available in captions.
https://www.databricks.com/dataaisummit/speaker/paul-marsh/#	Paul Marsh - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPaul MarshSenior Director Application Development at New York JetsBack to speakersPaul Marsh is the Sr. Director of Application Development at the New York Jets. In his current role, Paul is responsible for the development and management of the Jets data infrastructure including its Databricks installation and the other technologies that make up the organization's data stack. Paul has been with the Jets organization for 19 years, including 14 years overseeing application development at the organization. Paul holds an BA in History from Binghampton University as well as a Masters of Science in E-Commerce from Fairleigh Dickinson University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
https://www.databricks.com/dataaisummit/speaker/slava-frid	Slava Frid - Data + AI Summit 2023 \| DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSlava FridCTO at WorldQuant PredictiveBack to speakersSlava is a 20+ year technology industry veteran who has led award-winning teams in finance, media, & non-profit sectors & enjoys pushing the envelope of what is considered possible. He is currently embracing the challenge of helping to build a new way to enable Quantitative Researchers to answer toughest questions businesses & organizations have. He received his degree in Econ from Wharton and a Computer Science degree from UPenn’s School of Engineering. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

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