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https://www.databricks.com/dataaisummit/speaker/mark-dandrea/#
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Mark D'Andrea - 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 ExperiencePricingMark D'AndreaGlobal Chief Revenue Officer at AccuweatherBack 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.
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https://www.databricks.com/try-databricks?itm_data=SiteWide-Footer-Trial
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Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations and RBAC.12x better price/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights
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https://www.databricks.com/dataaisummit/speaker/miranda-luna/#
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Miranda Luna - 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 ExperiencePricingMiranda LunaProduct Management at DatabricksBack to speakersMiranda focuses on making all aspects of the Databricks SQL experience delightful. She resides in Seattle where outside of work she can usually be found skiing or golfing.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/dataaisummit/speaker/siddharth-bhai/#
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Siddharth Bhai - 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 ExperiencePricingSiddharth BhaiSr. Manager, Product Management at DatabricksBack to speakersSiddharth Bhai is a product management leader at Databricks, with 15+ years of experience, including long stints at Google and Microsoft. He has deep experience in identity, security, provisioning, and cloud computing. He has spoken at major industry conferences, including Hybrid Identity Protection, Directory Experts Conference, Microsoft TechEd, and Google Cloud Next. This summer, he’s interested in hearing about how teams in the real world are using Databricks. Come say hi if you see him!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/product/workflows
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Databricks Workflows | Workflow Authoring, Deep Platform IntegrationSkip 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 NOWWorkflowsReliable orchestration for data, analytics and AITry for freeWhat is Databricks Workflows?The fully managed lakehouse orchestration service for all your teams to build reliable data, analytics and AI workflows on any cloud.Orchestrate any combination of notebooks, SQL, Spark, ML models and dbt as a Jobs workflow, including calls to other systems. Build ETL pipelines that are automatically managed, including ingestion and lineage, using Delta Live Tables. Databricks Workflows is available on GCP, AWS and Azure, giving you full flexibility and cloud independence.Orchestrate anything anywhereRun diverse workloads for the full data and AI lifecycle on any cloud. Orchestrate Delta Live Tables and Jobs for SQL, Spark, notebooks, dbt, ML models and more.Simple workflow authoringAn easy point-and-click authoring experience for all your data teams, not just those with specialized skills.Deep platform integrationDesigned and built into the Databricks Lakehouse Platform giving you deep monitoring capabilities and centralized observability across all your workflows.Proven reliabilityHave full confidence in your workflows leveraging our proven experience running tens of millions of production workloads daily across AWS, Azure and GCP.Fully managedRemove operational overhead with a fully managed orchestration service, so you can focus on your workflows not on managing your infrastructure.“Databricks Workflows allows our analysts to easily create, run, monitor and repair data pipelines without managing any infrastructure. This enables them to have full autonomy in designing and improving ETL processes that produce must-have insights for our clients. We are excited to move our Airflow pipelines over to Databricks Workflows.”— Anup Segu, Senior Software Engineer, YipitData“Databricks Workflows freed up our time dealing with the logistics of running routine workflows. With newly implemented repair/rerun capabilities, it helped to cut down our workflow cycle time by continuing the job runs after code fixes without having to rerun the other completed steps before the fix. Combined with ML models, data store and SQL analytics dashboard etc., it provided us with a complete suite of tools for us to manage our big data pipeline.”— Yanyan Wu, VP, Head of Unconventionals Data, Wood Mackenzie – A Verisk BusinessResources
All the resources you need. All in one place.
Explore the resource library to find eBooks and videos on the benefits of data engineering on Databricks.
Explore resourcesBlogsIntroducing Databricks WorkflowsIntroducing Repair and RerunDemosWorkflowsDelta Live TablesWebinarTackle Data Transformation With Delta Live TablesReady to get started?Sign up for accessDelta Live Tables documentationProductPlatform 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/dataaisummit/speaker/jeremy-lewallen
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Jeremy Lewallen - 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 ExperiencePricingJeremy LewallenProduct Manager at DatabricksBack to speakersJeremy Lewallen is a Staff Product Manager on DBSQL. He leads the the workload management, performance, control plane, API, and concurrency product direction.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/dataaisummit/speaker/michael-carbin
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Michael Carbin - 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 CarbinFounding Advisor, MosaicML and Associate Professor, Department of Electrical Engineering and Computer Science at Massachusetts Institute of TechnologyBack to speakersMichael Carbin is an associate professor in MIT’s Department of Electrical Engineering and Computer Science and a principal investigator at the Computer Science and Artificial Intelligence Laboratory, where he leads the Programming Systems Group. His group investigates the semantics, design, and implementation of systems that operate in the presence of uncertainty in their environment (perception), implementation (neural networks or approximate transformations), or execution (unreliable hardware). Carbin has received a Sloan Research Fellowship, a Facebook Research Award, a Google Faculty Research Award and an NSF Career Award. He earned a BS in computer science at Stanford University and an MS and PhD in electrical engineering and computer science from MITLooking 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/dataaisummit/speaker/antoni-baum
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Antoni Baum - 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 ExperiencePricingAntoni BaumSoftware Engineer at AnyscaleBack to speakersAntoni is a Software Engineer at Anyscale, working on Ray AIR and the rest of Ray ML ecosystem.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/it/company/partners/consulting-and-si/partner-solutions?itm_data=menu-item-brickbuildersoverview
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Soluzioni dei partner - 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 NOWSoluzioni dei partnerSoluzioni per migrazione e settori industriali specifici sviluppate dai partner per il lakehouseAbbiamo collaborato con i maggiori partner di consulenza per costruire soluzioni innovative per casi d'uso di migrazione e settori industriali specifici. Le Databricks Brickbuilder Solution sono concepite dai nostri partner per aiutare le aziende a ridurre i costi e aumentare il valore ricavato dai dati. Grazie alla pluriennale esperienza nel settore dei nostri partner e a soluzioni realizzate appositamente per Databricks Lakehouse Platform, ogni azienda può avere la certezza di trovare soluzioni su misura per la sua attività.Cerca partner attivisearchSettore pubblicoCloud Data Migration by Accenture - DatabricksMaggiori informazioniRetail e largo consumoUnified View of Demand by AccentureMaggiori informazioniTecnologie di pubblicità e marketingCPG Control Tower by AvanadeMaggiori informazioniTecnologie di pubblicità e marketingIntelligent Healthcare on Azure Databricks by AvanadeMaggiori informazioniTecnologie di pubblicità e marketingIntelligent ManufacturingMaggiori informazioniTecnologie di pubblicità e marketingLegacy System Migration by AvanadeMaggiori informazioniTecnologie di pubblicità e marketingRisk Management by AvanadeMaggiori informazioniTecnologia e softwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksMaggiori informazioniTecnologia e softwareMigrate to Cloud and Databricks by Capgemini and DatabricksMaggiori informazioniTecnologia e softwareCapgemini Revenue Growth ManagementMaggiori informazioniTecnologia e softwareMigrate to Databricks by Celebal Technologies and DatabricksMaggiori informazioniTecnologia e softwareCognizant Video Quality of ExperienceMaggiori informazioniTecnologie di pubblicità e marketingPersona 360 by DataSentics and DatabricksMaggiori informazioniTecnologie di pubblicità e marketingSAP Migration Accelerator by DataSentics - DatabricksMaggiori informazioniTecnologie di pubblicità e marketingPrecisionView™ by DeloitteMaggiori informazioniTecnologie di pubblicità e marketingTrellis by DeloitteMaggiori informazioniTecnologie di pubblicità e marketingSmart Migration to Databricks by EPAMMaggiori informazioniTecnologie di pubblicità e marketingLeapLogic Migration Solution by ImpetusMaggiori informazioniCARICA ALTRIPronto per cominciare?Prova Databricks gratisProdottoPanoramica 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
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https://www.databricks.com/solutions/industries/federal-government#videoinfo-6
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Federal Government Industry 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 NOWData analytics and AI for federal agenciesUnlock innovation to deliver better public services with data and machine learningFrom the Federal Data Strategy to the AI Executive Order, it’s clear that the U.S. federal government is focused on modernizing its data analytics and warehousing capabilities.The Databricks Lakehouse Platform empowers federal agencies to unlock the full potential of their data to deliver on their mission objectives and better serve citizens.Empowering Federal agencies to leverage data and AI to deliver on mission objectivesTrusted by leading public sector agencies+ Any other Apache Spark™️ compatible clientSee how industry leaders are using Databricks to improve the experience for citizens across all public servicesLatest blog posts, webinars, and case studiesWhy Databricks for the federal governmentModernize your data analytics130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Deliver mission outcomes effectively and efficiently130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Create better experiences for citizens130 char. Modernize your technology stack to improve experience for patients and physicians with the fastest DNAQSeq pipeline at scale.Learn moreExtensive compliance for quick and easy approval to operate (ATO)Databricks has achieved ATOs on the regions, networks and compliance controls that support your mission objectivesCloudsC2S
SC2S
GovCloud
Public Cloud
NetworksPublic
NIPR
SIPR
JWICS
Compliance controlsFedRAMP
FedRAMP-High
FISMA
IL5
IL6
ICS-503
How Databricks fuels innovation for the federal governmentHealthcareImprove the delivery and quality of healthcare services for citizens with powerful analytics and a 360° view of patients.
Patient 360
Supply chain optimization
Insurance management Genomics
Drug discovery and deliveryDefenseApply the power of predictive analytics to geospatial, IoT and surveillance data to improve operations and protect the nation.
Logistics
Predictive maintenance
Surveillance and reconnaissance
Law enforcement and readinessHomeland SecurityDetect and prevent criminal activities and national threats with real-time analytics and data-driven decision-making.
Customs and border protection
Immigration and citizenship
Counter-terrorism
Federal emergency aid managementPublic Authority/CommerceProactively detect anomalies with machine learning to mitigate risk and prevent fraudulent activity.
Tax fraud and collection
Process and operations management
Grants management
Customer 360EnergyImprove energy management with data insights that ensure energy resiliency and sustainability.
Security of energy infrastructure
Smarter energy management
Energy exploration
Electrical grid reliabilityIntelligence CommunityLeverage real-time insights to make informed decisions that can impact the safety of our citizens and the world.
Threat detection
Neutralize cyberattacks
Intelligence surveillance and reconnaissance
Social media analyticsResourcesCustomer StoriesDriving Digital Transformation to Put Patients First at CMSData Governance Best Practices — Lessons Learned From the Centers for Medicare and Medicaid ServicesLessons Learned From Modernizing the USCIS Data Analytics PlatformModernizing the Air Force With Big Data and AIWebinarsRapid Response to Hospital Operations Using Data and AI During COVID-19Geospatial Analytics and AI in the Public SectorModern Data Analytics Architecture for the GovernmentImproving Threat Detection With Big Data and AINewsAzure Databricks Achieves FedRAMP High Authorization on Microsoft Azure Government (MAG)Government-Grade Security in the AWS CloudBringing Unified Analytics to Government ClientsEmpowering the U.S. Intelligence Community With Mission-Critical Analytics and AISummit talksAutomating the Federal Aviation Administration’s (FAA) System-Wide Information Management (SWIM) Data Ingestion and AnalysisGeospatial Analytics at Scale: Analyzing Human Movement Patterns During a PandemicReady to get started?We’d love to understand your business goals and how our services team can help you succeed. Try for freeContact usProductPlatform 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/dataaisummit/speaker/andria-fuquen
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Andria Fuquen - 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 ExperiencePricingAndria FuquenTechnical Program Manager at ImmutaBack to speakersAndria Fuquen is a Technical Program Manager at Immuta, a data security focused company. She has over 7 years of experience across engineering, data systems, governance and security. At Immuta, her role is to help customers achieve success through their onboarding phase and become empowered to further streamline their data security practices. Ms. Fuquen is a strong advocate for diversity and supporting women in tech, proudly representing the Latina community. When not working, Andria enjoys spinning vinyl records and perfecting her salsa moves.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/dataaisummit/speaker/denny-lee
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Denny Lee - 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 ExperiencePricingDenny LeeSr. Staff Developer Advocate at DatabricksBack to speakersDenny is a Databricks Developer Advocate. A hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale data platforms, and predictive analytics systems. He also has a Masters of Biomedical Informatics from Oregon Health and Sciences University and has implemented powerful data solutions for enterprise Healthcare customers. His current technical focuses include Distributed Systems, Apache Spark, Deep Learning, Machine Learning, and Genomics.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/dataaisummit/speaker/noritaka-sekiyama/#
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Noritaka Sekiyama - 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 ExperiencePricingNoritaka SekiyamaPrincipal Big Data Architect at Amazon Web ServicesBack to speakersNoritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team at Amazon Web Services. He has more than 10 years of experience working in the software industry. Based in Tokyo, Japan, he is responsible for implementing software artifacts, building libraries, troubleshooting complex issues and helping guide customer architectures.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/solutions/accelerators/real-time-bidding-optimization
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Real-Time Bidding Optimization - Databricks World's Lakehouse Platform | 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 AcceleratorReal-Time Bidding OptimizationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook
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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”). These Terms expressly do not govern your access to or use of the Databricks Platform Services (known as Databricks and Databricks Community Edition, each located at *.cloud.databricks.com, or the related website at help.databricks.com and platform support services, together the “Platform Services”), which are subject to the Databricks Terms of Service (or with respect to the Community Edition, the Community Edition Terms of Service) or other written agreement in place between Databricks, Inc. (“Databricks”) and our subscribers (“Subscribers”) (any such agreement, a “Services Agreement”).PLEASE READ CAREFULLY THESE TERMS AND THE DATABRICKS PRIVACY POLICY (“PRIVACY POLICY”) WHICH IS INCORPORATED BY REFERENCE INTO THESE TERMS. BY ACCESSING OR USING ANY OF THE SITES, YOU REPRESENT THAT YOU ARE AT LEAST 18 YEARS OLD, YOU ACKNOWLEDGE AND AGREE THAT YOU HAVE READ AND UNDERSTOOD THESE TERMS, AND YOU AGREE TO BE LEGALLY BOUND BY ALL OF THESE TERMS. IF YOU DO NOT AGREE TO ALL OF THESE TERMS, DO NOT ACCESS OR USE THE SITES. WE SUGGEST YOU PRINT A COPY OF THESE TERMS FOR YOUR RECORDS.Throughout the Terms, “we,” “us,” “our” and “ours” refer to Databricks, and “you,” “your” or “yours” refer to you personally (i.e., the individual who reads and agrees to be bound by these Terms) and, if you access the Sites on behalf of a legal entity, to that entity. If you are using the Sites on behalf of any entity you represent and warrant that you are authorized to accept these Terms on such entity’s behalf and, by accepting these Terms, you are hereby binding such entity to the Terms.Subject to your compliance with these Terms, solely for so long as you are permitted by Databricks to access and use the Sites, and provided that you keep intact all copyright and other proprietary notices, you may view Content and you may download and print the materials that Databricks specifically makes available for downloading from the Sites (such as white papers or user documentation), in each case solely for informational purposes and solely for personal or internal business use.ACCEPTANCE OF TERMS
Databricks provides the Sites to you conditioned upon your accepting all of the Terms, without modification. Your use of the Sites constitutes your agreement with such Terms. We reserve the right to change, modify, add to, or remove portions of these Terms in our sole discretion at any time and we will, at our sole discretion, either post the modification on https://www.databricks.com/terms-of-use or provide you with email notice of the modification. You should check these Terms periodically for changes and you can determine when these Terms were last revised by referring to the “Last Updated” reference at the top of these Terms. Any modification shall be effective immediately upon the uploading of modified Terms. You indicate your agreement to comply with, and be bound by, any such modification by continuing to use or access the Sites after modified Terms are posted. If the modified Terms are not acceptable to you, your sole recourse is to discontinue your use of the Sites.
If you have registered for and opened an account through the Sites (an “Account”), you are entirely responsible for maintaining the confidentiality of your Account information, including your password, and for any and all activity that occurs under your Account. You agree to notify Databricks immediately of any unauthorized use of your Account or password, or any other breach of security. However, you will remain responsible for losses incurred by Databricks or by any other party due to your knowingly or inadvertently permitting unauthorized use of your Account or your Account information. You may not use anyone else’s ID, password or account at any time unless we expressly pre-approve such use, or unless expressly permitted under a Services Agreement. Databricks cannot and will not be liable for any loss or damage arising from your failure to comply with these obligations. Registration for any account is void where the user lacks the requisite eligibility for registration or if such registration is otherwise prohibited.Software (“Software”) or the Platform Services may be made available to you through the Sites. Your rights to access and use the Platform Services, including any Software will be subject to your agreement to the applicable Services Agreement governing your use of the Platform Services and to any terms and conditions of any applicable third party software license agreement (“Software License”) identified in the Software or on the web page providing access to the Software. You may not use any Software unless you agree to be bound by all terms and conditions of any applicable Software License. If there is a conflict between any Services Agreement and any Software License, the conflicting term of the Software License shall control but only to the extent necessary to eliminate the conflict.LICENSE GRANT AND PROPRIETARY RIGHTS
Provided that you fully comply at all times with these Terms and any other policies or restrictions posted on or transmitted through the Sites, Databricks grants you a limited, non-exclusive, non-transferable, revocable license to access and use the Sites. Except as otherwise specifically noted in these Terms or on the Sites, the Software, Submissions (as later defined), and all other information, content, user interfaces, graphics, registered or unregistered trademarks, logos, images, artwork, videos, and documents, and the design, structure, selection, coordination, expression, “look and feel” and arrangement of such materials, made available through the Sites (collectively, the “Content”), regardless of its source or creation, is owned, controlled or licensed by or to Databricks, and is protected by trade dress, copyright, patent and trademark laws, and various other intellectual property rights and unfair competition laws, and Databricks reserves and retains all rights in and to such Content. Any reproduction, redistribution or other use or exploitation of Software in violation of any applicable Software License or in violation of any license granted under these Terms or, if applicable, under a Services Agreement, is expressly prohibited by law, and may result in civil and criminal penalties.
“Apache” and “Spark” are trademarks of the Apache Software Foundation. Any other third party trademarks, service marks, logos, trade names or other proprietary designations, that are or may become present within the Sites, including within any Content, are the registered or unregistered trademarks of the respective parties.Except solely as necessary for you to access the Sites for the intended purpose pursuant to these Terms, you may not copy, collect, modify, create derivative works or uses of, translate, distribute, transmit, publish, re-publish, perform, display, post, download, upload, sublicense, transfer, dispose of, resell or sell the Content or any other part of the Services. Except as expressly set forth in these Terms, these Terms do not grant to you any license to any intellectual property rights or other proprietary rights, including any implied licenses or licenses granted by estoppel or otherwise.INFORMATION SUBMITTED THROUGH OR TO OUR SITES
At our sole discretion, you may be permitted to provide Submissions (as defined in the next sentence) to the Sites (e.g., through our forums). “Submissions” are defined to include: any messages, emails, text, graphics, code, questions, suggestions, comments, feedback, ideas, plans, notes, drawings, sample data, sound, images, video, original or creative materials, and other items or materials that you may provide to discussion forums, blogs, or other interactive features or areas of the Services where you or other users can create, post, transmit or store Content. Unless otherwise specifically agreed to by you and Databricks, by uploading, e-mailing, posting, publishing or otherwise transmitting any Submission, you hereby acknowledge that such Submission is non-confidential and you automatically grant (or warrant that the owner of such rights has expressly granted) to Databricks a perpetual, irrevocable, worldwide, non-exclusive, sub-licensable, fully paid-up and royalty-free license to use, make, have made, offer for sale, sell, copy, distribute, perform, display (whether publicly or otherwise), modify, adapt, publish, transmit and otherwise exploit such Submission, by means of any form, medium, or technology now known or later developed, and to grant to others rights to do any of the foregoing. In addition, you warrant that all so-called moral rights in such Submission have been waived.
For each Submission, you represent and warrant that you have all rights necessary for you to grant the license granted in the prior paragraph, and that such Submission, and your provision thereof to and through the Sites, does not violate any privacy, publicity, contractual, intellectual property, or other right or rights of any person or entity or otherwise violate any applicable laws, rules or regulations. You acknowledge that Databricks may have ideas or materials already under consideration or development that are or may be similar to your Submissions and that you are not entitled to any form of compensation or reimbursement from Databricks in connection with your Submissions. You agree to be fully responsible for, and to pay any and all royalties, fees, damages, and any other monies owing any person or entity by reason of, any Submission you provide to the Sites. We reserve the right to terminate access to all or any part of the Sites for anyone we suspect to be an infringer of our or any third party’s intellectual property rights of any kind whatsoever.You agree that you will not, and will not allow or authorize any third party to, post Submissions containing:Anything that is or may be (a) threatening, harassing, degrading, abusive or hateful; (b) an incitement to violence, terrorism or other wrongdoing; (c) defamatory or libelous; (d) invasive of privacy rights; (e) fraudulent, deceptive, impersonating of any person or entity, or misrepresentative of your affiliation with any person or entity; (f) obscene, pornographic, indecent, grotesque or otherwise objectionable; or (g) protected by copyright, trademark, confidentiality obligations, or other proprietary or privacy right without the express prior written consent of the owner of such right.Any material, the posting or usage of which would give rise to criminal or civil liability, or cause violation of any rules or regulations, or that encourages conduct that constitutes a criminal offense.Any virus, worm, Trojan horse or other computer code, file, data or program that is harmful, disruptive, corrupted, or invasive, or may be or is intended to damage or hijack the operation of any hardware or software.Any information identifiable to a particular individual, including but not limited to addresses, phone numbers, email addresses, birthdates, Social Security numbers and other government-issued identification numbers, payment card and other financial account numbers or login credentials, and health information.Any unsolicited or unauthorized advertising, promotional materials, junk mail, spam, chain letter, pyramid scheme, political campaign message, offering of an investment opportunity, or any other form of solicitation.Any material with respect to which you do not have all rights, power and authority necessary for its collection, use and processing, or where your use and provision to the Sites would breach any agreement between you and any third party.Databricks generally does not pre-screen or monitor Submissions (but reserves the right to do so) and does not control Submissions. Therefore, Databricks does not guarantee the accuracy, quality or appropriateness of Submissions and disclaims any responsibility for Submissions, including any liability for errors or omissions, or for any loss or damage of any kind incurred as a result of their use. However, Databricks reserves the right at its sole discretion to refuse, delete, screen or edit Submissions, provided that even if we do remove or alter any Submission, we shall have no obligation to stop our other uses of such Submission or any other Submission as permitted above. We have no obligation to store any of your Submissions. We have no responsibility or liability for the deletion or failure to store, transmit or receive your Submissions, nor do we have any responsibility for the security, privacy, storage or transmission of other communications originating with or involving your use of the Sites, except as may be expressly stated in these Terms or in the Privacy Policy. You are solely responsible for creating backup copies of and replacing any Submissions at your sole cost and expense. Our Privacy Policy governs your Submissions.By accepting these Terms, you agree to our collection, use, and disclosure of your information as described in the Privacy Policy. No one under age 18 may register for an Account or provide any personal information to Databricks or to the Sites. If we learn that we have collected personal information from or about anyone under age 18, we will delete that information as quickly as possible. If you believe that we might have any information from or about a child under 18, please contact us at [email protected] with the subject “Child Data“.Databricks reserves the right to disclose any Submissions, and the circumstances surrounding their transmission, to any third party to operate the Sites, to protect Databricks or its suppliers or representatives, to protect users of the Sites, to comply with legal or regulatory obligations, to enforce these Terms, or for any other reason. Databricks is not responsible or liable for the conduct of, or your interactions with, any other users of the Sites (whether online or offline), or for any associated loss, damage, injury or harm. By using the Site, you may be exposed to Submissions that are offensive, indecent or objectionable and you agree that Databricks bears no liability for such exposure.REQUIRED CONDUCT WHILE USING OUR SITES
While using the Sites you will comply with all applicable laws, rules and regulations. In addition, Databricks expects users of the Sites to respect the rights and dignity of others. Your use of the Sites is conditioned on your compliance with the rules of conduct set forth in this Section; any failure to comply may also result in termination of your access to the Sites pursuant to Section 9 (Suspension or Termination of Access to Our Sites). In using the Sites, you agree that you will not, and will not allow or authorize any third party to:
Use the Sites or any Content for any purpose that is illegal, fraudulent, deceptive or unauthorized by these Terms, or would give rise to civil liability, or to solicit the performance of any illegal activity or other activity which infringes the rights of Databricks or others, or to encourage or promote any such activity.Engage in or promote any conduct that is offensive, harassing, predatory, stalking, violent, threatening, discriminatory, racist, hateful, or otherwise harmful, against any individual or group.Harvest or collect information about any third parties, including their email addresses or other personally identifiable information.Send, by email or other means, any unsolicited or unauthorized advertising, promotional materials, junk mail, spam, chain letter, pyramid scheme, political campaign message, offering of an investment opportunity, or any other form of solicitation, or conceal or forge headers of emails or other messages, or otherwise misrepresent the identity of senders, for the purpose of sending spam or other unsolicited messages.Impersonate or post on behalf of, or express or imply the endorsement of, any individual or entity, including Databricks or any of its representatives, or otherwise misrepresent your affiliation with a person or entity.Use the Sites in any manner, whether deliberate or otherwise, including without limitation a denial of service attack, that could in any way (a) interfere with, damage, disable, overburden or impair the functioning of the Sites, or Databricks’ systems or networks, or any systems or networks connected to the Sites, or (b) violate any requirements, procedures, policies or regulations of such systems or networks.Operate non-permissioned network services, including open proxies, mail relays or recursive domain name servers, or use any means to bypass user limitations relating to the Sites.Use any robot, spider, crawler, scraper, deep-link, page-scrape, site search/retrieval application or other manual or automated device, program, algorithm or methodology or interface not provided by us to access, acquire, copy, retrieve, index, scrape, data mine, in any way reproduce or circumvent the navigational structure or presentation of the Sites or monitor any portion of the Sites or to extract data, or to sell, resell, frame, mirror or otherwise exploit for any commercial purpose, any portion of, use of, or access to the Sites (including any Content, Software and other materials available through the Sites), or attempt to circumvent any content filtering techniques we may employ.Remove any copyright, trademark or other proprietary rights notice from the Sites or from Content or other materials contained on or originating from the Sites.Create a database of any type by systematically downloading and storing any Content unless expressly permitted by Databricks to do so.Attempt to gain unauthorized access to any portion or feature of the Sites, or any other systems or networks connected to the Sites or to any Databricks server, or to any of the services offered on or through the Sites, by hacking, password mining or any other illegitimate means.Use or attempt to use any account you are not authorized to use.Probe, scan, monitor or test the vulnerability of the Sites or any network connected to the Sites, or breach the security or authentication measures on the Sites or any network connected to the Sites.Modify, adapt, create derivative works of, translate, reverse engineer, decompile or disassemble any portion of the Sites (including any Content or other materials available through the Sites), or do anything that might discover source code or bypass or circumvent measures employed to prevent or limit access to any area, Content or code within the Sites except as, and solely to the extent, expressly authorized under applicable law overriding any of these restrictions.Develop any third-party applications that interact with the Sites or Content without our prior written consent.Use or apply the Sites in any manner directly or indirectly competitive with any business of Databricks. LINKS
We may from time-to-time at our discretion host or provide links to services, products, web pages, websites or other content of third parties (“Third-Party Content”). The inclusion of any link to, or the hosting of, any Third Party Content is provided solely as a convenience to our users, including you, and does not imply affiliation, endorsement, approval, control or adoption by us of the Third-Party Content. We make no claims or representations regarding, and accept no responsibility or liability for, Third-Party Content including without limitation its quality, accuracy, nature, ownership or reliability. Your use of Third-Party Content is at your own risk. When you leave the Sites to access Third Party Content via a link, you should be aware that our policies, including the Privacy Policy, no longer govern. You should review the applicable terms and policies, including privacy and data gathering policies, of any website to which you navigate from the Sites.DISCLAIMER OF WARRANTIES
YOU EXPRESSLY AGREE THAT YOUR USE OF THE SITES, INCLUDING ANY CONTENT, IS AT YOUR SOLE RISK. ALL OF THE SITES AND CONTENT ARE PROVIDED TO YOU ON AN “AS IS” AND “AS AVAILABLE” BASIS, AND DATABRICKS MAKES NO RELATED REPRESENTATIONS, AND DISCLAIMS ALL POSSIBLE WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. WE DO NOT WARRANT THAT THE SITES OR CONTENT ARE ACCURATE, CONTINUOUSLY AVAILABLE, COMPLETE, RELIABLE, SECURE, CURRENT, ERROR-FREE, OR FREE OF VIRUSES OR OTHER HARMFUL COMPONENTS. DATABRICKS CANNOT AND DOES NOT GUARANTEE THAT ANY DEFECTS, ERRORS OR OMISSIONS WILL BE CORRECTED, REGARDLESS OF WHETHER DATABRICKS IS AWARE OF SUCH DEFECTS, ERRORS OR OMISSIONS.
TO THE EXTENT APPLICABLE STATE LAW DOES NOT ALLOW THE EXCLUSIONS AND DISCLAIMERS OF WARRANTIES AS SET FORTH IN THIS SECTION 6, SOME OR ALL OF THE ABOVE EXCLUSIONS AND DISCLAIMERS MAY NOT APPLY TO YOU, IN WHICH CASE SUCH EXCLUSIONS AND DISCLAIMERS WILL APPLY TO THE FULLEST EXTENT PERMITTED BY APPLICABLE LAW. YOU ACKNOWLEDGE THAT THE DISCLAIMERS, LIMITATIONS, AND WAIVERS OF LIABILITY SET FORTH IN THIS SECTION 6 SHALL SURVIVE ANY EXPIRATION OR TERMINATION OF THESE TERMS OR YOUR USE OF THE SITES.LIMITATION OF LIABILITY
YOU ACKNOWLEDGE AND AGREE THAT, TO THE MAXIMUM EXTENT PERMITTED BY LAW, THE ENTIRE RISK ARISING OUT OF YOUR ACCESS TO AND USE OF THE SITES AND CONTENT REMAINS WITH YOU. IN NO EVENT WILL DATABRICKS OR ANY OF ITS DIRECTORS, EMPLOYEES, AGENTS OR SUPPLIERS BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL, EXEMPLARY, CONSEQUENTIAL OR PUNITIVE DAMAGES OF ANY KIND (INCLUDING, BUT NOT LIMITED TO, LOSS OF USE, LOSS OF BUSINESS, LOSS OF PROFITS, LOSS OF DATA, LOSS OF GOODWILL, SERVICE INTERRUPTION, COMPUTER DAMAGE, SYSTEM FAILURE OR THE COST OF SUBSTITUTE PRODUCTS OR SERVICES) ARISING OUT OF OR IN CONNECTION WITH THE SITES, AND ANY CONTENT, SERVICES OR PRODUCTS INCLUDED ON OR OTHERWISE MADE AVAILABLE THROUGH THE SITES, REGARDLESS OF THE FORM OF ACTION (WHETHER IN CONTRACT, TORT, STRICT LIABILITY, EQUITY OR OTHERWISE) AND EVEN IF WE ARE AWARE OF OR HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
IN NO EVENT WILL OUR TOTAL CUMULATIVE LIABILITY TO YOU ARISING OUT OF OR IN CONNECTION WITH THESE TERMS, OR FROM THE USE OF OR INABILITY TO USE THE SITES, INCLUDING ANY CONTENT, OR FROM THE USE OF OR EXPOSURE TO ANY SUBMISSIONS, EXCEED ONE HUNDRED DOLLARS ($100.00). MULTIPLE CLAIMS WILL NOT EXPAND THIS LIMITATION.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. ADDITIONALLY, TO THE EXTENT APPLICABLE STATE OR OTHER LAW DOES NOT ALLOW THE EXCLUSIONS AND LIMITATIONS OF DAMAGES AS SET FORTH IN THIS SECTION 7, SOME OR ALL OF THE ABOVE EXCLUSIONS AND LIMITATIONS MAY NOT APPLY TO YOU, IN WHICH CASE DATABRICKS’ LIABILITY TO YOU WILL BE LIMITED BY THIS SECTION TO THE FULLEST EXTENT PERMITTED BY APPLICABLE LAW.THIS SECTION WILL BE GIVEN FULL EFFECT EVEN IF ANY REMEDY SPECIFIED IN THESE TERMS IS DEEMED TO HAVE FAILED OF ITS ESSENTIAL PURPOSE. THESE LIMITATIONS OF LIABILITY FORM AN ESSENTIAL BASIS OF THE BARGAIN BETWEEN THE PARTIES. YOU ACKNOWLEDGE THAT THE LIMITATIONS OF LIABILITY SET FORTH IN THIS SECTION 7 SHALL SURVIVE ANY TERMINATION OR EXPIRATION OF THESE TERMS OR YOUR USE OF THE SITES.INDEMNIFICATION
To the fullest extent permitted by law, you agree to indemnify, defend and hold harmless Databricks, its officers, directors, shareholders, successors in interest, employees, agents, subsidiaries and affiliates, from and against any and all actual or threatened third party claims (groundless or otherwise), demands, losses, damages, costs and liability, proceedings (at law or in equity) and expenses (including reasonable attorneys’ and expert fees and costs of investigation) arising out of or in connection with (a) your use of the Sites, including without limitation any of your Submissions, (b) your breach of these Terms, including your breach of any covenant, representation, warranty, term, or condition set forth herein, including, without limitation, the obligations set forth in Section 3 (Information Submitted Through Our Sites) and Section 4 (Required Conduct While Using Our Sites), (c) your violation of any law or regulation or of any third party rights, including infringement, libel, misappropriation, or other violation of any third party’s intellectual property or other legal rights or (d) the disclosure, solicitation or use of any personal information by you, whether with or without your knowledge or consent. Databricks reserves the right, however, to assume the exclusive defense and control of any matter otherwise subject to indemnification by you and, in such case, you agree to cooperate with Databricks’ defense of such claim, and in no event may you agree to any settlement affecting Databricks without Databricks’ prior written consent.SUSPENSION OR TERMINATION OF ACCESS TO OUR SITES
Notwithstanding any provision to the contrary in these Terms, you agree that Databricks may, in its sole discretion and with or without prior notice, for any or no reason, suspend or terminate your access to any or all of the Sites and/or block your future access to any or all of the Sites, including without limitation for any of the following reasons: (a) if we determine that you have violated any provision, or the spirit, of these Terms, (b) in response to a request by a law enforcement or other government agency, (c) due to discontinuance or material modification of any of the Sites, or (d) due to unexpected technical issues or problems. Databricks shall not be liable to you or any third party for any termination of your access to any part of the Sites. The rights and obligations of these Terms which by their nature should survive, shall so survive any termination of your use of the Sites.CONTACT
Questions or comments about the Terms or about the Sites may be directed to Databricks at the email address [email protected] You may also email us at that address if you would like to report what you believe to be a violation of these Terms. However, please note that we do not accept any responsibility to maintain the confidentiality of any report of a violation you may submit to us, including your identity, nor do we commit to providing a personal reply to any report you submit, nor are we obligated to take action in response to your report.CLAIMS OF COPYRIGHT INFRINGEMENT
Databricks respects the intellectual property rights of others and we request that the people who use the Sites do the same. The Digital Millennium Copyright Act of 1998 (the “DMCA”) provides recourse for copyright owners who believe that material appearing on the Internet infringes their rights under U.S. copyright law. If you believe in good faith that materials available on the Sites infringe your copyright, you (or your agent) may send Databricks a notice requesting that we remove the material or block access to it. If you believe in good faith that someone has wrongly filed a notice of copyright infringement against you, you may send a counter-notice to Databricks under applicable provisions of the DMCA. Please note that substantial penalties under U.S. copyright law may be levied against any filer of a false counter-notice. Notices and counter-notices must meet the then-current statutory requirements imposed by the DMCA. See 17 U.S.C. § 512(c)(3), available at https://www.copyright.gov/title17/92chap5.html for details. Notices and counter-notices should be sent to:
Attn: Legal Department/DMCA Copyright Agent
Databricks, Inc.
160 Spear Street, Suite 1300
San Francisco, CA 94105
[email protected]
(866) 330-0121You should note that if you knowingly misrepresent in your notification that the material or activity is infringing, you will be liable for any damages, including costs and attorneys’ fees, incurred by us or the alleged infringer as the result of our relying upon such misrepresentation in removing or disabling access to the material or activity claimed to be infringing. We encourage you to consult your legal advisor before filing a notice or counter-notice.In accordance with the DMCA and other applicable law, Databricks may at our discretion limit access to the Sites and/or terminate the accounts of any users who infringe any intellectual property rights of others, whether or not there is any repeat infringement.GENERAL
The Terms and the relationship between each user and Databricks shall be governed by the laws of the State of California without regard to its conflict of law provisions and each party shall submit to the personal and exclusive jurisdiction of the courts located in San Francisco, California. The application of the United Nations Convention on Contracts for the International Sale of Goods is expressly excluded. Except to the extent a Services Agreement applies, these Terms, along with the Privacy Policy, constitute the entire agreement between you and Databricks with respect to your use of the Sites and supersede all prior or contemporaneous communications and proposals, whether electronic, oral or written, between you and Databricks with respect to the Sites. If any provision of the Terms is found by a court of competent jurisdiction to be invalid, the parties nevertheless agree that the court should endeavor to give effect to the parties’ intentions as reflected in the provision, and the other provisions of the Terms remain in full force and effect. A party may only waive its rights under these Terms by a written document executed by both parties. Databricks’ failure to insist on or enforce strict performance of these Terms shall not be construed as a waiver by Databricks of any provision or any right it has to enforce these Terms, nor shall any course of conduct between Databricks and you or any other party be deemed to modify any provision of these Terms. The headings of the sections of these Terms are for convenience of reference only and are not intended to restrict, affect or be of any weight in the interpretation or construction of the provisions of such sections.
None of your rights or duties under these Terms may be transferred, assigned or delegated by you without our prior written consent, and any attempted transfer, assignment or delegation without such consent will be void and without effect. We may freely transfer, assign or delegate any of our rights or duties under these Terms. Subject to the foregoing, these Terms will be binding upon and will inure to the benefit of the parties and their respective representatives, heirs, administrators, successors and permitted assigns. No provision of these Terms is intended for the benefit of any third party, and the parties do not intend that any provision should be enforceable by a third party. Our relationship is an independent contractor relationship, and neither these Terms nor any actions by either party may be interpreted as creating an agency or partnership relationship. Nothing in these Terms shall be construed to obligate Databricks to enter into or engage with you on any commercial transaction.If you are provided access to any Software, you acknowledge that such Software may be subject to regulation by local laws and United States government agencies which prohibit export or diversion of certain products or information about products to certain countries and certain persons. You represent and warrant that you will not export or re-export such Software in violation of these regulations.You acknowledge that your breach of any of the provisions of these Terms may cause immediate and irreparable harm to Databricks for which we may not have an adequate remedy in money damages. We will therefore be entitled to obtain an injunction against such breach from any court of competent jurisdiction immediately upon request and will be entitled to recover from you the costs incurred in seeking such an injunction. The availability or exercise of our right to obtain injunctive relief will not limit our right to seek or obtain any other remedy.You agree that we will not be liable for delays, failures, or inadequate performance of the Sites resulting from conditions outside of our reasonable control, including but not limited to natural disasters or other acts of God, failure of telecommunications networks or any other network or utility, threatened or actual acts of terrorism or war, riots, labor strikes, or governmental acts or orders.Last Updated May 25, 2018ProductPlatform 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
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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/dataaisummit/speaker/volker-tjaden
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Volker Tjaden - 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 ExperiencePricingVolker TjadenManager Solution Architects at DatabricksBack to speakersVolker leads a team of Solutions Architects at Databricks. His career in Data & AI started out as an economics student at university where he focused on statistical and computational methods working with large datasets. After completing a PhD, he held various consulting and management positions in different industries where he built data driven solutions to business problems such as dynamic pricing in banking, automated supply chains in retail and IoT platforms in manufacturing.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/dataaisummit/speaker/gidon-gershinsky
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Gidon Gershinsky - 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 ExperiencePricingGidon GershinskyLead Systems Architect at AppleBack to speakersGidon Gershinsky designs and builds Data Security solutions at Apple. He plays a leading role in the Apache Parquet community work on big data encryption and integrity verification technologies.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/solutions/accelerators/medicare-risk-adjustment
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Automate Medicare Risk Adjustments With NLP | 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 AcceleratorMedicare Risk AdjustmentPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedIdentify undiagnosed conditions for reimbursementsIn the United States, the Centers for Medicare & Medicaid Services (CMS) reimburses private Medicare insurers based on beneficiary risk. Most insurers rely on claims data to calculate member risk, but that provides a narrow, point-in-time view of health. To address this gap, Databricks and John Snow Labs Solution Accelerator for Medicare Risk Adjustment automates the extraction of undiagnosed member conditions from unstructured clinical notes with NLP models, improving downstream reimbursements.Detect undiagnosed conditions in unstructured text with NLPAppend ICD-10 and HCC codes with pretrained modelsCalculate revised RAF scores to improve reimbursementsDownload notebookResourceseBookRead nowOn-demand webinarWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform 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/dataaisummit/speaker/don-bosco-durai/#
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Don Bosco Durai - 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 ExperiencePricingDon Bosco DuraiCofounder and CTO at PrivaceraBack to speakersBosco is an enterprise security thought leader. Bosco co-founded XASecure which reinvented security at scale for Big Data which later became Apache Ranger. Bosco is currently co-founder and CTO at Privacera addressing data security & access governance challenges in the Cloud. He is also actively involved in the Open-Source communities as a committer in open source projects like Apache Ranger, Ambari, and HAWQ.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/dataaisummit/speaker/scott-castle/#
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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/product/photon
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Photon | 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 NOWPhotonThe next generation engine for the LakehouseGet startedLearn morePhoton is the next generation engine on the Databricks Lakehouse Platform that provides extremely fast query performance at low cost – from data ingestion, ETL, streaming, data science and interactive queries – directly on your data lake. Photon is compatible with Apache Spark™ APIs, so getting started is as easy as turning it on – no code changes and no lock-in.Cheaper and fasterBuilt from the ground up for the fastest performance at lower cost, Photon provides up to 80% TCO savings while accelerating data and analytics workloads — up to 12x speedups.Built for all use casesPhoton is the first engine that enables data teams to standardize on one set of APIs for all workloads — ETL, analytics and data science — in batch or streaming.No code changesPhoton is an ANSI-compliant engine designed to be compatible with modern Apache Spark APIs and just works with your existing code — SQL, Python, R, Scala and Java — no rewrite required.Why Photon?Query performance on Databricks has steadily increased over the years, powered by Apache Spark and thousands of optimizations packaged as part of the Databricks Runtimes (DBR). Photon — a new native vectorized engine entirely written in C++ — provides an additional 2x speedup per the TPC-DS 1TB benchmark, and customers have observed 3x–8x speedups on average, based on their workloads, compared to the latest DBR versions.Use casesProduction jobsAccelerate large-scale production jobs on SQL and Spark DataFramesIoT applicationsFaster time-series analysis using Photon compared to Spark and traditional Databricks RuntimeData privacy and complianceQuery petabyte-scale data sets to identify and delete records without duplicating data with Delta Lake, production jobs and PhotonLoading data into Delta Lake and ParquetPhoton’s vectorized I/O speeds up data loads for Delta Lake and Parquet tables, lowering overall runtime and the cost of data engineering jobsHow does it work?Best price/performance for analytics in the cloudWritten from the ground up in C++, Photon takes advantage of modern hardware for faster queries, providing up to 12x better price/performance compared to other cloud data warehouses — all natively on your data lake.Works with your existing code and avoids vendor lock-inPhoton is designed to be compatible with the Apache Spark DataFrame and SQL APIs to ensure workloads run seamlessly without code changes. All you have to do to benefit from Photon is turn it on. Photon will seamlessly coordinate work and resources and transparently accelerate portions of your SQL and Spark queries. No tuning or user intervention required.Optimizing for all data use cases and workloadsWhile we started Photon primarily focused on SQL to provide customers with world-class data warehousing performance on their data lakes, we’ve significantly increased the scope of ingestion sources, formats, APIs and methods supported by Photon since then. As a result, customers have seen dramatic infrastructure cost savings and speedups on Photon across all their modern Spark workloads (e.g., Spark SQL and DataFrame).Discover moreDelta LakeDatabricks SQLUnity CatalogDelta Live TablesResources
All the resources you need. All in one place.
Explore the resource library to find eBooks and videos on the benefits of data engineering on Databricks.
Explore resourcesPapersPhoton: A Fast Query Engine for Lakehouse Systems (SIGMOD Paper)EventsHow AT&T Data Science Team Solved an Insurmountable Big Data Challenge on Databricks with Two Different Approaches using Photon and RAPIDS Accelerator for Apache SparkRadical Speed on the Lakehouses: Photon under the hoodRadical Speed for SQL Queries on Databricks: Photon Under the HoodBlogsApache Spark and Photon Receive SIGMOD AwardsDatabricks Sets Official Data Warehousing Performance RecordNew Performance Improvements in Databricks SQLAnnouncing Photon Public Preview: The Next-Generation Query Engine on the Databricks Lakehouse PlatformReady 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
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https://www.databricks.com/dataaisummit/speaker/aayush-patel
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Aayush Patel - 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 ExperiencePricingAayush PatelData & Platform Engineer at SkywatchBack to speakersAayush is a data and platform engineer at Skywatch, where he focuses on developing robust data platforms and scalable data products. He specializes in creating high-fidelity data systems and is currently working on building a collaborative enterprise solution for large organizations to purchase and share earth observation data. Aayush has previously built data frameworks, such as a no-code reporting platform that leverages a centralized metrics catalog to generate uniform data reports.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/dataaisummit/speaker/elliot-shmukler/#
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Elliot Shmukler - 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 ExperiencePricingElliot ShmuklerCo-Founder & CEO at AnomaloBack to speakersElliot Shmukler is the co-founder and CEO at Anomalo, where he and the team are building software to help data teams detect and root cause issues in their data before anyone else notices. Before starting Anomalo, Elliot has long championed using data to make decisions and build products as a senior Silicon Valley executive at companies like Instacart, Wealthfront, LinkedIn, and eBay. Elliot is a recognized Silicon Valley expert in data-driven product management and consumer growth strategies.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/dataaisummit/speaker/junta-nakai/#
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Junta Nakai - 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 ExperiencePricingJunta NakaiRVP, Industry Solutions, Financial Services and Sustainability 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.
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https://www.databricks.com/it/solutions/industries/financial-services
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Lakehouse per servizi finanziari | 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 NOWLakehouse per servizi finanziariPotenziare le future istituzioni di servizi finanziari guidate da dati e AICominciaProgramma una demoQuattro problematiche di gestione
dei dati nei servizi finanziariGovernance e gestione dei dati
La mancanza di agilità dei dati e riproducibilità dei modelli ostacola il rispetto dei requisiti normativi specifici dei servizi finanziari.Conoscenza più approfondita dei clienti
I silos di dati impediscono di avere una vista completa del comportamento dei clienti, delle opportunità di cross-selling e delle informazioni necessarie per una personalizzazione diffusa su larga scala.Decisioni in tempo reale
Quando si è vincolati a un fornitore e si utilizzano strumenti scollegati, diminuisce la capacità di fare analisi in tempo reale per supportare e democratizzare scelte finanziarie più intelligenti.Accesso ai dati di terze parti
Le tecnologie tradizionali non consentono di ricavare informazioni approfondite su finanza e clienti da set di dati non strutturati e alternativi che crescono velocemente e, inoltre, non offrono funzionalità di condivisione di dati aperti per promuovere la collaborazione.Lakehouse per servizi finanziariPiattaforma unificata per dati e AI
Una piattaforma unificata che riunisce tutti i carichi di lavoro di gestione e analisi dei dati per realizzare innovazioni trasformative nelle moderne istituzioni di servizi finanziari.
Soluzioni dei partner
I principali fornitori mondiali stanno sviluppando soluzioni per la lakehouse per servizi finanziari. I clienti potranno così sfruttare offerte preconfigurate per accelerare la trasformazione guidata dai dati.
Strumenti per accelerare i risultati del business
Databricks e i suoi partner hanno creato una gamma completa di acceleratori che semplificano la realizzazione di casi d'uso comuni nei servizi finanziari, dagli investimenti ESG alla lotta alle frodi.
Collaborazione con il settore
Condivisione di dati sicura e aperta con il nostro ecosistema di dati (che comprende S&P Global, Intercontinental Exchange, FactSet e Nasdaq) per realizzare innovazioni che favoriscono la creazione di valore sostenibile.
Trasformare i servizi finanziari con
la piattaforma lakehouse
“La visione della gestione dei dati e dell'AI del Nasdaq si fonda su Databricks Lakehouse. Utilizziamo la piattaforma per elaborare enormi quantità di dati finanziari e alternativi complessi, per generare nuovi dati e informazioni approfondite per i nostri clienti. Databricks svolge un ruolo importante anche per il nostro obiettivo di ammodernare la fornitura e il consumo di dati. La soluzione ci consente di inviare i dati direttamente agli spazi di lavoro di analisi, in modo che i clienti possano analizzare e integrare dati mission-critical senza dover trasferire continuamente terabyte di dati."— Bill Dague, Head of Nasdaq Data Link, NasdaqPerché la piattaforma lakehouse per servizi finanziari?
Unificare dati e AI su una piattaforma aperta e collaborativa che consente di ridurre al minimo il rischio, offrire ai clienti esperienze superiori e accelerare l'innovazioneApproccio governato alla gestione del rischio e alla conformità
Semplificare la complessità della reportistica normativa, della gestione del rischio e della conformità, snellendo in modo sicuro l'acquisizione, l'elaborazione e la trasmissione di dati per realizzare pratiche migliori di governance dei dati.Prodotti e servizi personalizzati
Unificare una grande varietà di dati (dai dati di mercato ai dati alternativi) per offrire esperienze iper-personalizzate che promuovono le opportunità di cross-selling, la soddisfazione del cliente e la quota di portafoglio.Informazioni approfondite in tempo reale per decisioni più efficaci
La rapida acquisizione di dati da tutte le sorgenti su larga scala consente di migliorare le scelte di investimento, individuare velocemente nuove frodi e applicare funzionalità in tempo reale alle pratiche di gestione del rischio.Condivisione di dati aperti e monetizzazione dei dati
Raccogliere grandi quantità di dati interni e di terze parti per condividere soluzioni finanziarie innovative, monetizzare nuovi prodotti di dati e fornire funzionalità di analisi avanzate per qualsiasi cloud o strumento senza vincolarsi a tecnologie proprietarie.Scarica l'eBookPartner e soluzioniPuntare su formati aperti e standardizzazione dei dati per analisi e AIGestione del rischioIntegrare velocemente i dati in modelli di valore a rischio per restare al passo con rischi e minacce emergenti.CominciaModernizzazione delle carte esistenti e dei portafogli bancari principaliEffettua una conversione rapida da sorgenti esterne e sviluppa capacità di conversione completamente configurabili e industrializzate.CominciaPersona 360Completa, unifica e cattura profili di clienti in un modello intelligente per la gestione dei dati.CominciaScopri tutte le soluzioni dei partnerSicurezza informatica su larga scalaIndividuare velocemente le minacce, investigare l'impatto e ridurre i rischi con Splunk e DatabricksCominciaPunteggio ESGAdottare una visione quantitativa della sostenibilità e garantire che le aziende rispondano delle loro azioniCominciaGestione del rischio modernaAdottare un approccio più agile alla gestione del rischio unificando i dati e l'IA nel LakehouseCominciaIndividuazione di frodi con analisi e AI geospazialiAnalizzando i dati geospaziali si possono comprendere meglio i comportamenti di spesa dei clienti, in particolare chi sono e come operano in bancaCominciaArricchimento delle transazioni con classificazione merceologicaAutomatizzando l'arricchimento delle transazioni, si può comprendere meglio il comportamento dei clienti e portare la personalizzazione all'estremoCominciaModelli AI basati su regole per combattere le frodi finanziarieRinnovare le strategie antifrode per ridurre i costi operativi e aumentare la fiducia dei clientiCominciaTrasmissione puntuale e affidabile di report normativiCombinare modelli di dati del settore dei servizi finanziari con il cloud per implementare standard di governance elevati con una spesa di sviluppo contenutaCominciaModernizzare le piattaforme con dati di investimentiSfruttare tutta la potenza dei dati del mercato finanziario per focalizzarsi sulla fornitura di prodotti ai clientiCominciaAntiriciclaggio (AML)Realizzare casi d'uso basati su AI come abbinamenti casuali (fuzzy match) e analisi di immagini per combattere il riciclaggio di denaro e il terrorismo finanziarioCominciaVedi tutte le soluzioniLakehouse per servizi finanziari in azioneVincere insieme: Dati + AI promuovono la collaborazione nel lakehouseREGISTRATI SUBITO →Risorse
Tutte le risorse di cui hai bisogno in un unico posto.
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Esplora risorseeBook e infografiche[Infografica] Dati per ancorare una nuova era della gestione del rischioScopri come è facile sfruttare il potenziale di dati e AI nei servizi finanziariSfruttare dati alternativi e di terze parti nei servizi finanziari →ESG dalla teoria alla pratica con l'analisi dei dati e l'AI Prevenire le frodi con Dati + AI: Istruzioni per combattere le minacce moderne → Video e downloadMetodologie per investimenti ESG spiegabili e trasparenti →Sicurezza informatica nei servizi finanziari →Accelerare l'innovazione guidata da dati e AI nei servizi finanziari →Analisi ESG: video esplicativo →Modernizzare la gestione del rischio →Moderne piattaforme di investimento con il Lakehouse for Financial Services →Scheda della soluzione Industry Lakehouse BlueprintsBlogAccelerator per banche e fintech che utilizzano le transazioni con carta di creditoUn approccio guidato dai dati ai fattori ESG (ambientale, sociale, governance) →Costruire una moderna piattaforma per la gestione del rischio nei servizi finanziari →Usare i dati per porre fine alle frodi sulle carte di credito: Capital One e altre best practice →Strategie per ammodernare le piattaforme di gestione dei dati di investimento →Migliorare l'esperienza del cliente con l'arricchimento delle transazioni → Suggerimenti preziosi per i servizi finanziari dal Data + AI Summit 2022 →Lakehouse per servizi finanziariPronto 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.
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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
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https://www.databricks.com/dataaisummit/speaker/eric-peter
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Eric Peter - 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 ExperiencePricingEric PeterSr Staff Product 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.
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https://www.databricks.com/glossary/mlops
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What is MLOps?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 NOWMLOpsAll>MLOpsWhat is MLOps?MLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. MLOps is a collaborative function, often comprising data scientists, devops engineers, and IT.What is the use of MLOps?MLOps is a useful approach for the creation and quality of machine learning and AI solutions. By adopting an MLOps approach, data scientists and machine learning engineers can collaborate and increase the pace of model development and production, by implementing continuous integration and deployment (CI/CD) practices with proper monitoring, validation, and governance of ML models.Why do we need MLOps?Productionizing machine learning is difficult. The machine learning lifecycle consists of many complex components such as data ingest, data prep, model training, model tuning, model deployment, model monitoring, explainability, and much more. It also requires collaboration and hand-offs across teams, from Data Engineering to Data Science to ML Engineering. Naturally, it requires stringent operational rigor to keep all these processes synchronous and working in tandem. MLOps encompasses the experimentation, iteration, and continuous improvement of the machine learning lifecycle.What are the benefits of MLOps?The primary benefits of MLOps are efficiency, scalability, and risk reduction. Efficiency: MLOps allows data teams to achieve faster model development, deliver higher quality ML models, and faster deployment and production. Scalability: MLOps also enables vast scalability and management where thousands of models can be overseen, controlled, managed, and monitored for continuous integration, continuous delivery, and continuous deployment. Specifically, MLOps provides reproducibility of ML pipelines, enabling more tightly-coupled collaboration across data teams, reducing conflict with devops and IT, and accelerating release velocity. Risk reduction: Machine learning models often need regulatory scrutiny and drift-check, and MLOps enables greater transparency and faster response to such requests and ensures greater compliance with an organization's or industry's policies.What are the components of MLOps?The span of MLOps in machine learning projects can be as focused or expansive as the project demands. In certain cases, MLOps can encompass everything from the data pipeline to model production, while other projects may require MLOps implementation of only the model deployment process. A majority of enterprises deploy MLOps principles across the following:Exploratory data analysis (EDA)Data Prep and Feature EngineeringModel training and tuningModel review and governanceModel inference and servingModel monitoringAutomated model retrainingWhat are the best practices for MLOps?The best practices for MLOps can be delineated by the stage at which MLOps principles are being applied.Exploratory data analysis (EDA) - Iteratively explore, share, and prep data for the machine learning lifecycle by creating reproducible, editable, and shareable datasets, tables, and visualizations.Data Prep and Feature Engineering- Iteratively transform, aggregate, and de-duplicate data to create refined features. Most importantly, make the features visible and shareable across data teams, leveraging a feature store.Model training and tuning - Use popular open source libraries such as scikit-learn and hyperopt to train and improve model performance. As a simpler alternative, use automated machine learning tools such as AutoML to automatically perform trial runs and create reviewable and deployable code.Model review and governance- Track model lineage, model versions, and manage model artifacts and transitions through their lifecycle. Discover, share, and collaborate across ML models with the help of an open source MLOps platform such as MLflow.Model inference and serving - Manage the frequency of model refresh, inference request times and similar production-specifics in testing and QA. Use CI/CD tools such as repos and orchestrators (borrowing devops principles) to automate the pre-production pipeline.Model deployment and monitoring - Automate permissions and cluster creation to productionize registered models. Enable REST API model endpoints.Automated model retraining - Create alerts and automation to take corrective action In case of model drift due to differences in training and inference data.What is the difference between MLOps and DevOps?MLOps is a set of engineering practices specific to machine learning projects that borrow from the more widely-adopted DevOps principles in software engineering. While DevOps brings a rapid, continuously iterative approach to shipping applications, MLOps borrows the same principles to take machine learning models to production. In both cases, the outcome is higher software quality, faster patching and releases, and higher customer satisfaction.Does training large language models (LLMOps) differ from traditional MLOps?While many of the concepts of MLOps still apply, there are other considerations when training large language models like Dolly. Let’s go through some of the key points where training LLMs might differ from the traditional MLOps approach:Computational Resources: Training and fine-tuning large language models typically involves performing orders of magnitude more calculations on large data sets. To speed this process up, specialized hardware like GPUs are used for much faster data-parallel operations. Having access to these specialized compute resources becomes essential for both training and deploying large language models. The cost of inference can also make model compression and distillation techniques important.Transfer Learning: Unlike many traditional ML models that are created or trained from scratch, many large language models start from a foundation model and are fine-tuned with new data to improve performance in a more specific domain. Fine-tuning allows state-of-the-art performance for specific applications using less data and fewer compute resources.Human Feedback: One of the major improvements in training large language models has come through reinforcement learning from human feedback (RLHF). More generally, since LLM tasks are often very open-ended, human feedback from your application’s end users is often critical for evaluating LLM performance. Integrating this feedback loop within your LLMOps pipelines can often increase the performance of your trained large language model.Hyperparameter Tuning: In classical ML, hyperparameter tuning often centers around improving accuracy or other metrics. For LLMs, tuning also becomes important for reducing the cost and computational power requirements of training and inference. For example, tweaking batch sizes and learning rates can dramatically change the speed and cost of training. Thus, both classical ML and LLMs benefit from tracking and optimizing the tuning process, but with different emphases.Performance Metrics: Traditional ML models have very clearly defined performance metrics, such as accuracy, AUC, F1 score, etc. These metrics are fairly straightforward to calculate. When it comes to evaluating LLMs, however, a whole different set of standard metrics and scoring apply — such as bilingual evaluation understudy (BLEU) and Recall-Oriented Understudy for Gisting Evaluation (ROGUE) that require some extra considering when implementing. What is an MLOps platform?An MLOps platform provides data scientists and software engineers with a collaborative environment that facilitates iterative data exploration, real-time co-working capabilities for experiment tracking, feature engineering, and model management, as well as controlled model transitioning, deployment, and monitoring. An MLOps automates the operational and synchronization aspects of the machine learning lifecycle.Try Databricks - a fully managed environment for MLflow - the world's leading open MLOps Platform. https://www.databricks.com/try/databricks-free-mlAdditional ResourcesTake your ML projects from planning to productionMLOps for DummiesThe Big Book of Machine Learning Use CasesBack 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
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https://www.databricks.com/dataaisummit/speaker/james-demmel/#
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James Demmel - 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 ExperiencePricingJames DemmelDr. Richard Carl Dehmel Distinguished Professor at University of California, BerkeleyBack to speakersProf. James Demmel is a Distinguished Professor of Mathematics and Computer Science at the University of California, Berkeley. He is the former chair of the Computer Science Division and EECS Department of UC Berkeley. Demmel is known for his work on numerical linear algebra libraries, including LAPACK, ScaLAPACK and SuperLU. Demmel’s work on high-performance computing, such as communication-avoiding algorithms, has been recognized by many honors and awards. He is a member of the National Academy of Sciences, National Academy of Engineering, American Academy of Arts and Sciences; Fellow of the AAAS, ACM, AMS, IEEE, and SIAM; ACM Paris Kanellakis Theory and Practice Award, IPDPS Charles Babbage Award, IEEE Sidney Fernbach Award, 13 best paper prizes. Demmel was one of just two scientists honored the Leslie Fox Prize for Numerical Analysis in 1986 and he was the winner of the J.H. Wilkinson Prize in Numerical Analysis and Scientific Computing, the IEEE's Sidney Fernbach Award "for computational science leadership in creating adaptive, innovative, high-performance linear algebra software", and the IEEE Computer Society Charles Babbage Award.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/dataaisummit/speaker/eric-schmidt/#
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Eric Schmidt - 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 ExperiencePricingEric SchmidtFormer CEO and Chairman, Google; Co-Founder at Schmidt FuturesBack to speakersEric Schmidt is an accomplished technologist, entrepreneur and philanthropist. He joined Google in 2001 and helped grow the company from a Silicon Valley startup to a global leader in technology alongside founders Sergey Brin and Larry Page. Eric served as Google’s Chief Executive Officer and Chairman from 2001–2011, as well as Executive Chairman and Technical Advisor. Under his leadership, Google dramatically scaled its infrastructure and diversified its product offerings while maintaining a strong culture of innovation. In 2017, he co-founded Schmidt Futures, a philanthropic initiative that bets early on exceptional people making the world better. Eric founded the Special Competitive Studies Project in 2021, a nonprofit initiative focused on strengthening America’s long-term AI and technological competitiveness in national security, the economy and society.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/it/company/partners/technology-partner-program
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Databricks Technology Partner Program - 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 NOWProgramma Partner TecnologiciEntra in contatto con migliaia di clienti di Databricks pronti a utilizzare il tuo prodottoIscrivitiDatabricks si integra con i migliori prodotti per dati e AI e li promuove sul mercato. Offriamo ai nostri partner supporto tecnico e commerciale per acquisire nuovi clienti ed espandere l'attività.Vantaggi per i partner tecnologiciIncentivi alle venditeIncentivi alla struttura operativa di Databricks per promuovere la vendita dei tuoi prodottiAccesso ai clientiAcquisisci direttamente nuovi clienti con Databricks Partner ConnectMaggiori informazioniSupporto per il marketingAccedi a risorse di marketing per allargare il tuo raggio d'azioneAccesso al team di prodotti e R&DAccesso al personale di Databricks per prodotti, progettazione e supportoAmbiente di prova gratuitoCostruisci e testa in un ambiente di prova gratuito (sandbox)Programmi di marketing congiuntoPartecipa a programmi di marketing congiunto con DatabricksPronto per lavorare insieme?IscrivitiTrova un partnerProdottoPanoramica 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
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https://www.databricks.com/dataaisummit/speaker/sumesh-nair
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Sumesh Nair - 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 ExperiencePricingSumesh NairDirector of Engineering, Data and Cloud Strategy at Optum, United HealthGroupBack to speakersExperienced and Accomplished senior IT leader with a 20-year track record of excellence. An Agile enthusiast with a history of transforming organizations to optimize product engineering & delivery. A servant-leader known for building high-performing teams to discover new solutions, challenge norms, and gain competitive advantages in the market. An experienced leader with P&L Oversight background, multi-channel product leadership, and driving organizational change by exceeding expectations.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/company/partners/consulting-and-si/partner-solutions/infosys-data-wizard-migrations
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Data Wizard for Hadoop/EDW Migrations by Infosys | 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 NOWBrickbuilder SolutionData Wizard for Hadoop/EDW Migrations by InfosysMigration solution developed by Infosys and powered by the Databricks Lakehouse Platform
Get startedConfidently move your data to DatabricksInfosys Data Wizard is a comprehensive solution with a set of accelerators for seamless data migration. It makes data warehouse and data lake migrations to the Databricks Lakehouse Platform seamless, secure, manageable, quick and risk-free. It offers an intuitive graphical user interface that is designed to follow execution approaches through different phases of migration — from project initiation to configuration, inventory collection, analysis, migration, validation, all the way through data certification, tracking and management. With Infosys Data Wizard, you can achieve:A 50%–60% acceleration in the data migration lifecycleA 30% reduction in the cost of migrationsA risk-free migration with comprehensive data certificationGet startedDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform 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
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Matthew Doxey - 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 DoxeySenior Epidemiologist at Washington State Department of HealthBack to speakersMatt Doxey is a public health data scientist with the Washington State Department of Health's Center for Data Science, where he leads data science and disease modeling initiatives. An epidemiologist by training with experience in global health initiatives and improving health outcomes in under-served communities, Matt is passionate about using innovative, data-driven methods and technologies to protect and enhance community and population health through better data.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/2021/11/18/build-your-business-on-databricks-with-partner-connect.html
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Build Your Business on Databricks With 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 SectorBuild Your Business on Databricks With Partner Connectby Dave Eyler, Pankaj Dugar and Zaheera ValaniNovember 18, 2021 in Platform BlogShare this postAt Databricks we believe that to create the ultimate customer experience, we must leverage the work of more than just our employees and create a platform others can extend. To see the importance of this, think of the apps on your phone. Were they all made by Apple or Google? How much less valuable would your phone be if that’s all you had?
That’s why today we are announcing the launch of Partner Connect that brings together the best data, analytics, and AI tools in one place for our customers to discover and integrate with. We’ve designed Partner Connect to meet the needs of both customers and partners, because that’s the only way we can create a virtuous cycle that will continue to grow and generate value for both groups.
Partner Connect is not just a list of logos, it’s a deep integration into Databricks that is directly visible and accessible to Databricks customers, and this is what makes it so valuable. By making their products available in Partner Connect, our partners can expect three key benefits that will help them build their businesses.
New leadsWith thousands of existing customers using the Databricks Lakehouse Platform and more joining every day, our partners in Partner Connect can expect significantly more inbound connections. Whether that means new customers or increased consumption from your existing customers, it’s a win either way.
Deep integrationPartner Connect creates a seamless experience for Databricks customers to create a new free trial account of our partners’ products AND automatically connect that account to their Databricks workspace. That means Databricks customers can find your product, create an account in your system, and play with your product with their Databricks Lakehouse already connected. How does it work? Partner Connect was built to invoke our partner’s APIs to establish connections, create accounts and pass details for the connection back to Databricks. The hardest parts of onboarding have been automated.
Visibility & confidenceWe want our sales teams and our partners to work and co-sell together. By putting your product in Partner Connect, it serves as a clear signal to the market that your product’s connection to Databricks Is built on a deep, quality integration. That means customer champions, our sales teams, and our partners can recommend it with full confidence, and that makes all the difference.
We look forward to working with you! If you would like to discuss adding your product to Partner Connect, please visit the Partner Connect registration page.Try Databricks for freeGet StartedSee 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
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https://www.databricks.com/learn
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Learn | 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 NOWLearnDive in and explore a world of Databricks resources — at your fingertips. You’ll find training and certification, upcoming events, helpful documentation and more.Getting started with DatabricksLearn the BasicsThe Databricks Lakehouse Platform makes it easy to build and execute data pipelines, collaborate on data science and analytics projects and build and deploy machine learning models. Check out our Getting Started guides below.New to Databricks? Start your journey with Databricks guided by an experienced Customer Success Engineer.Databricks onboarding
Lakehouse Fundamentals Training
Watch 4 short videos, take the quiz and get your badge
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Get startedData science and engineeringDatabricks AdministratorsSQL analyticsMachine learningTrainingGet trained through Databricks Academy. Learn how to master data analytics from the team that started the Apache Spark™ research project at UC Berkeley.Databricks AcademyCertificationCertification exams assess how well you know the Databricks Lakehouse Platform and the methods required to successfully implement quality projects. They help you gain industry recognition, competitive differentiation, greater productivity and results, and a tangible measure of your educational investment.Databricks CertificationGet Your Questions AnsweredChoose from the following ways to get clarity on questions that might come up as you are getting started:Ask a Databricks technical expert liveOnline CommunityExplore popular topics within the Databricks community.Connect with the communityPopular forum topicsDatabricksDelta LakeSparkSQLPySparkAzureAWSGCPNeed hands on help?If you have a support contract or are interested in one, check out our options below. For strategic business guidance (with a Customer Success Engineer or a Professional Services contract), contact your workspace Administrator to reach out to your Databricks Account Executive.Check out our support optionsNotebook GalleryThis gallery showcases some of the possibilities through Notebooks focused on technologies and use cases which can easily be imported into your own Databricks environment or the free community edition.Databricks Notebook GalleryDocumentationThe Databricks technical documentation site provides how-to guidance and reference information for the Databricks data science and engineering, Databricks machine learning and Databricks SQL persona-based environments.AWS documentationAzure documentationGoogle documentationDatabricks events and communityData + AI SummitJoin us for keynotes, product announcements and 200+ technical sessions — featuring a lineup of experts in industry, research and academia.Learn moreGlobal eventsSave your spot at one of our global or regional conferences, live product demos, webinars, partner-sponsored events or meetups.Learn moreData + AI online meetupsFind out what’s happening at Databricks Meetup groups around the world and join one near or far — all virtually.Learn moreBeaconsMeet the Databricks Beacons, a group of community members who go above and beyond to uplift the data and AI community.Learn moreUniversity AllianceJoin the Databricks University Alliance to access complimentary resources for educators who want to teach using Databricks.Learn moreData Brew VidcastExploring Data + AI With ExpertsBrooke Wenig and Denny LeeVideo SeriesOnline Tech Talks and MeetupsBrooke Wenig and Denny LeeTech TalksManaging the Complete Machine Learning Lifecycle Using MLflowJules DamjiTech TalksGetting Started With Delta LakeDenny LeeTech TalksDiving Into Delta Lake (Advanced)Denny LeeDatabricks Demo Hub (Product Demos)Data + AI ResearchMatei ZahariaCo-Founder and Chief TechnologistDatabricksReynold XinCo-Founder and Chief ArchitectDatabricksSue Ann HongSoftware EngineerDatabricksRead recent papers from Databricks founders, staff and researchers on distributed systems, AI and data analytics — in collaboration with leading universities such as UC Berkeley and Stanford.Access researchProductPlatform 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/dataaisummit/speaker/menglei-sun
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Menglei Sun - 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 ExperiencePricingMenglei SunSenior Software Engineer at DatabricksBack to speakersMenglei Sun is a senior software engineer at Databricks working on data lineage and data discovery related projects. Previously, Menglei worked at Houzz, BlackRock on data infrastructure, data engineering and platform.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/dataaisummit/speaker/murali-madireddi
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Murali Madireddi - 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 ExperiencePricingMurali MadireddiArchitect at AccentureBack to speakersMurali is an accomplished architect with strong expertise in ETL, DW and Data lakes.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/company/careers/open-positions?department=operations
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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
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https://www.databricks.com/privacy
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Privacy Notice | 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 UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates ( “Databricks”, “we”, “our”, and “us”) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the “Sites”), our data processing platform products and services (the “Platform Services”) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, “Databricks Services”). It also contains information about your choices and privacy rights.Our ServicesWe provide the Platform Services to our customers and users (collectively, “Customers”) under an agreement with them and solely for their benefit and the benefit of personnel authorized to use the Platform Services (“Authorized Users”). Our processing of such data is governed by our agreement with the relevant Customer. This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities. We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes. Information we collect automatically We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information). For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications. The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our Cookie Notice. When you use our Platform Services, we automatically collect information about how you are using the Platform Services (“Usage Data”). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. We collect Usage Data to provide, support and operate the Platform Services, for network and information security, and to better understand how our Authorized Users and Customers are using the Platform Services to improve our products and services. We may also use the information we collect automatically (for example, IP address, and unique device identifiers) to identify the same unique person across Databricks Services to provide a more seamless and personalized experience to you. Information we receive from other sourcesWe may obtain information about you from third party sources, including resellers, distributors, business partners, event sponsors, security and fraud detection services, social media platforms, and publicly available sources. Examples of information that we receive from third parties include marketing and sales information (such as name, email address, phone number and similar contact information), and purchase, support and other information about your interactions with our Sites and Platform Services. We may combine such information with the information we receive and collect from you.How We Use Your InformationWe use your personal information to provide, maintain, improve and update our Databricks Services. Our purposes for collecting your personal information include:to provide, maintain, deliver and update the Databricks Services;to create and maintain your Databricks account;to measure your use and improve Databricks Services, and to develop new products and services;for billing, payment, or account management; for example, to identify your account and correctly identify your usage of our products and services;to provide you with customer service and support;to register and provide you with training and certification programs;to investigate security issues, prevent fraud, or combat the illegal or controlled uses of our products and services;for sales phone calls for training and coaching purposes, quality assurance and administration (in accordance with applicable laws), including to analyze sales calls using analytics tools to gain better insights into our interactions with customers; to send you notifications about the Databricks Services, including technical notices, updates, security alerts, administrative messages and invoices;to respond to your questions, comments, and requests, including to keep in contact with you regarding the products and services you use;to tailor and send you newsletters, emails and other content to promote our products and services (you can always unsubscribe from our marketing emails by clicking here) and to allow third party partners (like our event sponsors) to send you marketing communications about their services, in accordance with your preferences;to personalize your experience when using our Sites and Platform Services;for advertising purposes; for example, to display and measure advertising on third party websites;to contact you to conduct surveys and for market research purposes;to generate and analyze statistical information about how our Sites and Platform Services are used in the aggregate;for other legitimate interests or lawful business purposes; for example, customer surveys, collecting feedback, and conducting audits;to comply with our obligations under applicable law, legal process, or government regulation; andfor other purposes, where you have given consent.How We Share Your InformationWe may share your personal information with third parties as follows:with our affiliates and subsidiaries for the purposes described in this Privacy Notice;with our service providers who assist us in providing the Databricks Services, such as billing, payment card processing, customer support, sales and marketing, and data analysis, subject to confidentiality obligations and the requirement that those service providers do not sell your personal information;with our service providers who assist us with detecting and preventing fraud, security threats or other illegal or malicious behavior, for example Sift who provides fraud detection services where your personal information is processed by Sift in accordance with its Privacy Notice available at https://sift.com/service-privacy;with third party business partners, such as resellers, distributors, and/or referral partners, who are involved in providing content, products or services to our prospects or Customers. We may also engage with third party partners who are working with us to organize or sponsor an event to which you have registered to enable them to contact you about the event or their services (but only where we have a lawful basis to do so, such as your consent where required by applicable law);with marketing partners, such as advertising providers that tailor online ads to your interests based on information they collect about your online activity (known as interest-based advertising);with the organization that is sponsoring your training or certification program, for example to notify them of your registration and completion of the course;when authorized by law or we deem necessary to comply with a legal process;when required to protect and defend the rights or property of Databricks or our Customers, including the security of our Sites, products and services (including the Platform Services);when necessary to protect the personal safety, property or other rights of the public, Databricks or our Customers;where it has been de-identified, including through aggregation or anonymization;when you instruct us to do so;where you have consented to the sharing of your information with third parties; orin connection with a merger, sale, financing or reorganization of all or part of our business.International TransfersDatabricks may transfer your personal information to countries other than your country of residence. In particular, we may transfer your personal information to the United States and other countries where our affiliates, business partners and services providers are located. These countries may not have equivalent data protection laws to the country where you reside. Wherever we process your personal information, we take appropriate steps to ensure it is protected in accordance with this Privacy Notice and applicable data protection laws. These safeguards include implementing the European Commission’s Standard Contractual Clauses for transfers of personal information from the EEA or Switzerland between us and our business partners and service providers, and equivalent measures for transfers of personal information from the United Kingdom. Databricks also offers our Customers the ability to enter into a data processing addendum (DPA) that contains the Standard Contractual Clauses, for transfers between us and our Customers. We also make use of supplementary measures to ensure your information is adequately protected. Privacy Shield NoticeDatabricks adheres to the principles of the EU-U.S. and Swiss-U.S. Privacy Shield Frameworks, although Databricks no longer relies on the EU-U.S. or Swiss-U.S. Privacy Shield Frameworks as a legal basis for transfers of personal information in light of the judgment of the Court of Justice of the European Union in Case C-311/18. To learn more, visit our Privacy Shield Notice.Your Choices and RightsWe offer you choices regarding the collection, use and sharing of your personal information and we will respect the choices you make in accordance with applicable law. Please note that if you decide not to provide us with certain personal information, you may not be able to access certain features of the Sites or use the Platform Services.Account informationIf you want to correct, update or delete your account information, please log on to your Databricks account and update your profile.Opt out of marketingWe may periodically send you marketing communications that promote our products and services consistent with your choices. You may opt out from receiving such communications, either by following the unsubscribe instructions in the communication you receive or by clicking here. Please note that we may still send you important service-related communications regarding our products or services, such as communications about your subscription or account, service announcements or security information.Your privacy rightsDepending upon your place of residence, you may have rights in relation to your personal information. Please review the jurisdiction specific sections below, including the disclosures for California residents. Depending on applicable data protection laws, those rights may include asking us to provide certain information about our collection and processing of your personal information, or requesting access, correction or deletion of your personal information. You also have the right to withdraw your consent, to the extent we rely on consent to process your personal information. If you wish to exercise any of your rights under applicable data protection laws, submit a request online by completing the request form here or emailing us at [email protected]. We will respond to requests that we receive in accordance with applicable laws. 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. 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How Amgen Modernized Its Analytics With a Unified Data Lakehouse - 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.
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For 40 years, we’ve pioneered new drug-making processes and developed life-saving medicines, positively impacting the lives of millions around the world. In order to continue fulfilling our mission to best serve patients, we recently embarked on another journey of innovation: a complete digital transformation.In the process of reimagining how to leverage our data for better outcomes across the business — from improving R&D productivity to optimizing supply chains and commercialization — it quickly became obvious that the types of problems our data teams were looking to solve had drastically changed in the last handful of years. Additionally, these problems were no longer isolated by skillset, department or function. Instead, the most impactful problems were cross-functional in nature and required bringing together people with different, unique expertise to attack problems in a novel way. In our quest to modernize, we chose the Databricks Lakehouse Platform as the foundation for our digital transformation journey. As a result, we were able to unlock the potential of our data across various organizations, streamlining operational efficiency and accelerating drug discovery.Today, we are sharing our success story in the hopes that others can learn from our journey and apply it to their own business strategies.From data warehouse to data lake – and the problems withinWithin three core verticals of Amgen - clinical trials, manufacturing, and commercialization – lies a wealth of valuable data. But increasing volumes of data presented challenges when it came to actually using that data efficiently.We were unable to truly weave together the various aspects of our business, which impacted operational efficiency as we scaled both internally and in our number of customers. The key was to not only make it easy to access and process data but to do so in a collaborative manner that ties in different personas that have different viewpoints on the data — a connected data fabric that enables better cross-functional collaboration. If you’re only looking at it from one or two perspectives, you’re going to miss valuable key points from others.For example, consider the question: How do you granularly forecast demand so you can produce the right amount of therapeutics for patients in need?If you’re looking at the answer from a supply chain and manufacturing perspective, you’re missing commercial sales forecast data. On the other hand, you don’t want to take the commercial sales forecast as the gospel of the amount of production needed because what if they blow their sales numbers out of the water, which is always the hope, and you’ve underestimated what manufacturing needs to produce?In order to solve today’s problems, businesses need to focus on different data relationships and connections so that they can look at the same data from multiple lenses — but how can they enable this? At Amgen, we’ve broken the foundation of modern data requirements down as follows:Data needs to be organized and easy to use.Sharing data and re-using that of others in a natural way is a must.Analytics should be able to operate off a trusted shared view of data.Different forms of analytics from descriptive (BI) to predictive (ML) helps facilitate new discoveries and predictions on one version of the data.Data needs to be able to evolve as new types are brought in, changes from one system to another occur, new domains are added, etc. but the core of it all should remain consistent.The need for this to be the case is likely known by most organizations, but seeing it come to life has been particularly difficult for enterprises with counter-intuitive processes: each team owning, managing and organizing their data differently, requiring yet another project if they simply want to share it. We too struggled with not only several years of accumulating more data than we knew what to do with, but also with the lack of process and infrastructure to ensure everyone was able to work off the same data.To try and address our early data needs, we transitioned from a legacy technology infrastructure over to a Hadoop-based data lake a few years back. With a Hadoop data lake, we were able to keep structured and unstructured data in one place, but significant data challenges remained, both on the technical side and when it came to processes, cost and organization. The shared clusters caused “Noisy Neighbor” problem and were difficult and costly to scale.For my role, as a product owner of the platform, managing a single shared cluster was a nightmare. It was always on, there was never a good time to upgrade versions, and we had distributed costs which meant, for example, figuring out how to charge one group for high storage and low compute and another group for high compute and low storage.This approach also required stitching together a variety of different tools in order to meet the needs of each individual group, which created significant collaboration challenges. And like so many others, we had a variety of ways that end-users were consuming data: Jupyter Notebooks, R Studio, Spotfire and Tableau, which only added to the complexity and challenge of making data readily available to those that need it.How the lakehouse architecture solves our problemsAdopting the Databricks Lakehouse Platform has enabled a variety of teams and personas to do more with our data. With this unifying and collaborative platform, we’ve been able to utilize a single environment for all types of users and their preferred tools, keeping operations backed by a consistent set of data.We’re leveraging Delta Lake to enable ACID compliance, historical lookback, and lower the barrier to entry for developers to begin coding by providing a common data layer for data analysts and data scientists alike to use data to optimize supply chains and improve operations. We’re also leveraging AWS Glue to connect different Databricks environments together so it’s one data lake – whether the data is stored in one AWS account or 10 different accounts. It’s all connected.This has enabled us to provide sufficient flexibility for a variety of needs while standardizing on Apache Spark™ for data and analytics. The unified data layer within the lakehouse allows Amgen to reliably process data of any type and size, while providing the application teams with the flexibility to move the business forward.What size clusters do you want? How much do you want to spend? Is it more important to get your reports an hour faster, or to cut costs? Decisions like these can now be made by individual teams. Collectively, this standardization of tools and languages, and a single source of truth for data scientists, analysts, and engineers, is what started enabling connected teams.Our current data architecture uses an Amazon S3 as the single source of truth for all data, Delta Lake as the common data layer, the Glue data catalog as the centralized metastore for Databricks, an ELK stack for monitoring with Kibana, Airflow for orchestration, and consumption, whether it’s analysts or data scientists, all operating off the Databricks Lakehouse Platform.This common data architecture, and integrating these architectural patterns has enabled us to shift our focus from platform maintenance to really digging into what the business actually wants and what our users care about. The key has been our ability to leverage the lakehouse approach to unify our data across our various data teams while aligning with our business goals.With data at the ready, various data teams from engineering to data science to analysts can access and collaborate on data. Databricks’ collaborative notebooks support their programming language of choice to easily explore and start leveraging the data for downstream analytics and ML. As we start to use Databricks SQL, our analysts can find and explore the latest and freshest data without having to move it into a data warehouse. They can run queries without sacrificing performance, and easily visualize results with their tools of choice — either through built-in visualizations and dashboards or Tableau, which is primarily used by business partners throughout the company.Our data scientists also benefit from using Databricks Machine Learning to simplify all aspects of ML. And since Databricks ML is built on the lakehouse foundation with Delta Lake and MLflow, our data scientists can prepare and process data, streamline cross-team collaboration and standardize the full lifecycle from experimentation to production without depending on data engineering support. This improved approach to managing ML has had a direct impact on decreasing the time it takes to enroll in clinical trials.Improving patient outcomes with connected data and teamsThe implementation of the Databricks Lakehouse Platform has ultimately helped us continue to achieve our goals of serving patients and improving the drug development lifecycle in a modern world. Our data ingestion rates have increased significantly, improving processing times by 75% resulting in 2x faster delivery of insights to the business, all while reducing compute costs by ~25% over static Hadoop clusters.With Databricks, we can take a modern approach to deliver on a myriad of use cases by focusing on the data, the relationships, and the connections rather than just the technology. Since partnering with Databricks in 2017, we’ve seen massive growth adoption across the company. To date, 2,000+ data users from data engineering to analysts have accessed 400TB of data through Databricks to support 40+ data lake projects and 240 data science projects.What this looks like in practice is easy to use, easy to find data that enables a number of use cases across the company:Genomic exploration and research at scale: Harnessing the power of genomic data has allowed us to accelerate the drug discovery process this could significantly increase our chances to find new drugs to cure grievous illnesses.Optimized clinical trial designs: Now we can bring in a variety of data from purchased data to real-world evidence, and leverage insights from this wide variety of clinical data to improve the likelihood of success and potentially save tens of millions of dollars.Supply chain and inventory optimization: Manufacturing efficiency and inventory management is a challenge for every manufacturing industry, and drug manufacturing is no exception. Efficient manufacturing and optimized supply chain management can help save millions of dollars to the business, and help get the right drugs to the right patients at the right time.As Amgen’s success demonstrates, novel solutions to age-old problems require a refresh of a business’s platforms, tools, and methods of innovation. And as adoption continues to rise at Amgen, we’ll explore new ways to take advantage of the lakehouse approach to foster collaboration and transparency with tools like Delta Sharing. Another intriguing tool that could provide value is Delta Live Tables, which could help us simplify ETL development and management even more, as well as benefit our downstream data consumers. Ultimately, Databricks has helped us to move the starting line for advanced analytics, so we can spend more time-solving problems that can benefit the patients who need treatments, and less time rebuilding the foundational infrastructure that enables it.Next StepsLearn more about the Databricks Lakehouse for Healthcare and Life SciencesWatch the Amgen talk from a recent webinarTry Databricks for freeGet StartedRelated postsIntroducing Lakehouse for Healthcare and Life SciencesMarch 9, 2022 by Michael Sanky and Michael Ortega in News
Each of us will likely generate millions of gigabytes of health data in our lifetimes: medical and pharmacy claims, electronic medical records with...
Unlocking the Power of Health Data With a Modern Data LakehouseJuly 19, 2021 by Michael Ortega, Michael Sanky and Amir Kermany in Engineering Blog
A single patient produces approximately 80 megabytes of medical data every year. Multiply that across thousands of patients over their lifetime, and you're...
Improving Drug Safety With Adverse Event Detection Using NLPJanuary 17, 2022 by Amir Kermany, Michael Ortega, Moritz Steller, David Talby and Michael Sanky in Engineering Blog
Don't miss our upcoming virtual workshop with John Snow Labs, Improve Drug Safety with NLP, to learn more about our joint NLP solution...
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Databricks SQL | DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센 터웨비나 5월 18일 / 오전 8시(태평양 표준시)
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Register nowDatabricks SQL(DB SQL)은 Databricks 레이크하우스 플랫폼의 서버리스 데이터 웨어하우스로, 최대 12배 향상된 가격-성능으로 모든 SQL 및 BI 애플리케이션을 대규모로 실행할 수 있으며, 통합 거버넌스 모델, 개방적 형식 및 API, 원하는 도구를 지원하여 공급업체에 종속되지 않습니다.최고의 가격-성능비용이 절감되고, 최고의 가격-성능을 제공할 뿐만 아니라, 서버리스 덕분에 클라우드 인프라를 관리하거나 구성, 확대할 필요가 없습니다.거버넌스 기본 제공개방적 표준을 사용하여 모든 데이터에 대한 하나의 사본을 설정하고, 표준 SQL을 사용하여 모든 데이터 팀에서 하나의 통합 거버넌스 계층을 제공합니다.풍부한 에코시스템SQL 및 Fivetran, dbt, Power BI, Tableau 등의 도구와 Databricks를 함께 사용하여 모든 저장된 데이터를 수집, 변환 및 쿼리할 수 있습니다.사일로 해제모든 애널리스트가 더욱 빠르게 데이터에 액세스하여 데이터스트림 실시간 분석을 실행하고, BI에서 ML까지 원활한 진행이 가능합니다.어떻게 작동하나요?에코시스템과의 매끄러운 통합 사용 편이성 실시간 성능 중앙 집중형 거버넌스 개방적이고 신뢰할 수 있는 데이터 레이크 기반어디서나 손쉽게 데이터를 수집, 변환 및 오케스트레이션위치와 관계없이 어디서나 데이터로 작업이 가능합니다. 애널리스트와 분석 엔지니어는 턴키 기능을 사용하여 Fivetran으로 클라우드 스토리지에서 엔터프라이즈 애플리케이션(예: Salesforce, Google Analytics, Marketo)까지 모든 곳에서 데이터를 쉽게 수집할 수 있습니다. 클릭 한 번이면 됩니다. 또한, 레이크하우스에 내장된 ETL 기능으로 간단하게 종속성을 관리하고 저장된 데이터를 변환하거나 Databricks SQL에서 dbt 등의 자주 사용하는 도구를 통해 최적의 성능을 활용할 수 있습니다. "Databricks와 Fivetran을 함께 사용한 덕분에 매우 짧은 시간에 강력하고 현대적인 데이터 파이프라인을 구축할 수 있었습니다. Fivetran은 우리에게 필요한 커넥터와 통합 기능을 모두 갖추고 있었습니다."— Kreg Tool 인사이트 및 분석 부문 책임자자세히원하는 도구를 사용한 최신 분석 및 BITableau, Power BI, Looker 등의 가장 일반적으로 사용하는 BI 도구를 원활하게 지원합니다. 이제 애널리스트는 자주 사용하는 도구에서 가장 완전한 최신 데이터를 통해 새로운 비즈니스 인사이트를 발견할 수 있습니다. 그뿐만 아니라 Databricks SQL은 기본 내장된 SQL 편집기, 시각화, 대시보드를 사용해 모든 애널리스트가 함께 협력하여 인사이트를 쿼리하고 찾아서 공유할 수 있도록 지원합니다. "데이터를 손쉽게 확보할 수 있게 되면서 Power BI 대시보드 및 보고서에 가장 최신의 완전한 데이터를 사용하고 있다는 사실에 훨씬 더 큰 자신감을 갖게 되었습니다."— Jake Stone, ButcherBox 비즈니스 분석 부문 수석 관리자자세히서버리스 컴퓨팅으로 리소스 관리 제거Databricks SQL 서버리스는 레이크하우스에서 클라우드 인프라를 관리, 구성하거나 확장할 필요가 없어서 데이터팀이 자신의 일에 최선을 다할 수 있는 여유를 제공합니다. Databricks SQL 웨어하우스는 스토리지와는 분리하여 즉각적이고 탄력적인 SQL 컴퓨팅을 제공하며, 동시성이 높은 사용 사례에 대해 자동 확장하여 제한 없는 동시성을 제공합니다. "Databricks SQL Serverless에서 Databricks SQL의 기능을 사용하면서 인프라를 훨씬 더 효율적으로 사용할 수 있게 되었습니다."— R. Tyler Croy, Scribd 플랫폼 엔지니어링 부문 책임자자세히최고의 성능을 발휘하도록 설계Databricks SQL에는 수천 가지 최적화가 포함되어 있어 각종 도구, 쿼리 타입 및 실제 애플리케이션에 모두 최선의 성능을 제공할 수 있습니다. 여기에는 차세대 벡터화 쿼리 엔진 Photon이 포함되며, SQL 엔드포인트와 함께 사용하면 다른 클라우드 데이터 웨어하우스보다 최대 12배 가격-성능을 제공합니다. "Databricks 레이크하우스 플랫폼에서 분석을 실행하여 타겟 행동에서 인사이트를 도출하는 데 필요한 시간을 몇 주에서 몇 분으로 단축했습니다."— Stephane Caron, CBC/Radio-Canada 비즈니스 인텔리전스 부문 수석 이사자세히표준 SQL로 한 곳에서 모든 데이터 저장 및 관리개방적 형식 Delta Lake를 사용하여 모든 데이터에 하나의 사본을 설정함으로써 데이터 종속을 피하고, 레이크하우스에서 바로 분석과 ETL/ELT를 실행할 수 있습니다. 데이터를 이동하거나, 서로 분리된 시스템에 사본을 저장할 필요가 없습니다. 그런 다음, Databricks Unity Catalog를 사용하여 세분화된 거버넌스, 데이터 리니지, 표준 SQL로 모든 데이터를 손쉽게 발견, 보호하고 관리할 수 있습니다. "Databricks는 우리 비즈니스의 핵심이 되었고, Databricks의 레이크하우스 아키텍처는 실행 가능한 데이터에 액세스하여 이를 저장하고 공유할 수 있는 통합된 방식을 제공합니다."— Jagan Mangalampalli, Punchh 빅데이터 부문 책임자자세히레이크하우스 플랫폼에서 지원하는 공통적 데이터 기반 구축Databricks 레이크하우스 플랫폼은 모든 분석 데이터 요구 사항 등에 가장 완전하고 전체적인 데이터 웨어하우징 솔루션을 제공합니다. 클라우드 데이터 웨어하우스보다 매우 적은 비용으로 세계 최고의 성능을 활용할 수 있습니다. 대규모로 원본 데이터에서 실천 가능한 데이터를 얻는 속도를 높이고 배치와 스트리밍을 통합합니다. 또한, 레이크하우스를 사용하는 데이터 팀은 설명적 분석에서 예측적 분석까지 자연스럽게 이동하여 새로운 인사이트를 발견할 수 있습니다. "Databricks는 데이터 및 분석 팀이 ABN AMRO 전반의 데이터에 액세스하고 공유할 수 있는 단일 플랫폼을 제공하여 전사적으로 자동화를 추진하고 인사이트를 도출하는 ML 기반 솔루션을 제공합니다."— Stefan Groot, ABN AMRO 분석 엔지니어링 책임자자세히Databricks로 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 마이그레이션통합에코시스템과 매끄럽게 통합되므로 데이터 팀의 유연성이 극대화됩니다. Fivetran으로 비즈니스에 중요한 데이터를 입력하고, dbt로 변환하고, Power BI, Tableau 또는 Looker로 새로운 인사이트를 찾을 수 있습니다. 그 과정에서 전혀 기존 데이터 웨어하우스로 데이터를 이동할 필요가 없습니다.데이터 수집 및 ETL데이터 거버넌스BI 및 대시보드+ 여타 모든 Apache Spark™️ 호환 클라이언트"지금은 그 어느 때보다도 기업 조직에 변화하는 상황에 적응하기 위한 속도와 민첩성을 지원할 데이터 전략이 절실한 시기입니다. 기업들이 서둘러 데이터를 클라우드로 옮기면서, 데이터 레이크에서 분석을 수행하는 방식에 관한 관심이 높아지고 있습니다. Databricks SQL는 고객에게 필요한 성능, 안정성과 확장성을 완비한 대량의 데이터에서 인사이트를 얻게 되는 완전히 새로운 경험을 제고합니다. Databricks와 손을 잡고 그런 기회를 실현하게 되어 뿌듯한 기분입니다."—Francois Ajenstat, 최고 제품 책임자, Tableau고객 사례더 자세히 알아보기Delta LakePartner ConnectUnity CatalogDelta Live 테이블관련 콘텐츠
여러분에게 필요한 모든 리소스가 한 곳에 있습니다.
리소스 라이브러리에서 레이크하우스의 장점에 대한 eBook과 동영상을 찾아보세요.
리소스 둘러보기eBook데이터 웨어하우스의 아버지 Bill Inmon이 구축한 데이터 레이크하우스레이크하우스가 차세대 데이터 웨어하우스인 이유데이터, 분석 및 AI 거버넌스데이터 엔지니어링 Big Book왕초보를 위한 데이터 웨어하우스에서 데이터 레이크하우스로 마이그레이션이벤트Data + AI World Tour로 보는 레이크하우스의 내부 구조레이크하우스의 성능 튜닝 모범 사례 웨비나 – 쿼리의 수명 내에서Databricks SQL 무료 교육 – 온디맨드최고의 데이터 웨어하우스는 레이크하우스블로그Databricks, 공식 데이터 웨어하우징 성능 신기록 달성Databricks SQL 정식 출시Databricks에서 SQL 언어의 발전: Ansi 표준 기본 지원, 데이터 웨어하우스에서 간편한 지원Databricks에서 더욱 간단하게 dbt 배포Databricks 레이크하우스 플랫폼의 데이터 웨어하우징 모델링 기술 및 구현Databricks 레이크하우스에서 Fivetran 및 dbt를 활용하여 마케팅 분석 솔루션을 수축하는 방법시작할 준비가 되셨나요?무료 시험판사용해 보기커뮤니티 가 입제품플랫폼 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
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Databricks University | DatabricksDatabricks University AllianceMore educator resourcesIf you are new to the Databricks University community, the following resources may be helpful in getting you started teaching Databricks in both in-person and virtual classrooms: Try Databricks for freeTo begin the sign-up process for a full-featured 14-day trial (bring a credit card and your own cloud resources) or to sign up for the Community Edition which is focused on students and educational institutions who are just getting started with Apache Spark.Free community edition Learn the basic concepts behind Spark using Databricks in this tutorialYou will learn the basics of creating Spark jobs, loading data, and working with data. You’ll also get an introduction to running machine learning algorithms and working with streaming data. Databricks lets you start writing Spark queries instantly so you can focus on your data problems.Learn more Access free self-paced trainings available through Databricks AcademyDatabricks Academy is the training and certification organization at Databricks (must sign up with email address given to you by your educational institution).Learn more View Databricks use cases and industry solutionsUse case solutionsIndustry solutions Watch content on the Databricks YouTube channelFeaturing videos and live streams of tech talks and online meet-ups as well as introductory workshops for college students hosted by key Databricks engineers.See all our videosJoin the Databricks University AllianceProductPlatform 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
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Timothy Ahrens - 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 ExperiencePricingTimothy AhrensMessaging Design Division Chief at Department of StateBack to speakersTim Ahrens is a civil service employee with the U.S. Department of State and currently serves as the Division Chief for the Information Resource Management Operations Messaging Systems Office, Messaging Design Division. As MD Division Chief, he leads business process re-engineering, design, development, agile delivery, and tier 3 operational support for five enterprise products: SMART, eRecords, FOIA technology stack, CDS, and the CfA Data.State technology platform.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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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
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Extracting Oncology Insights from Real-World Clinical Data with NLP - 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
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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.
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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 SectorExtracting Oncology Insights From Real-World Clinical Data With NLPby Amir Kermany, Moritz Steller, David Talby and Michael SankySeptember 22, 2021 in Engineering BlogShare this postPreview the solution accelerator notebooks referenced in this blog online or get started right away by downloading and importing the notebooks into your Databricks account.Cancer is the leading cause of death and disease in the U.S., and the numbers are staggering with nearly 2 million new cases of cancer expected to be diagnosed in the U.S. this coming year. Cancer also represents a significant portion of total U.S. healthcare spending, estimated at more than $200B in 2020. As such, the biopharmaceutical industry is heavily focused on oncology drug development. Nearly 40 new cancer drugs were approved by the FDA in 2019 and 2020 alone, and more than 1300 new medications and vaccines are in clinical development.Measuring the efficacy of oncology interventions is critical to matching patients with the right intervention. Oncology data, and related real-world evidence, have the potential to inform clinical research, trial design, regulatory decisions, safety assessments, treatment pathways and more. Unfortunately, given the highly specialized nature of oncology care, disease criteria and endpoints typically are not available in structured formats and remain locked in data silos, making them hard to aggregate and analyze.In oncology, pathology reports (often captured in PDF format and siloed in EMR systems), contain critical information, such as tumor size, grade, stage and histology. These variables, once extracted with a natural language processing (NLP) system, can be used to define disease cohorts, assess disease severity and create a baseline for disease progression, which then can be applied to the aforementioned use cases, ranging from clinical trial matching to treatment pathways. But extracting this information from unstructured clinical text data is often a huge pain point for data teams.John Snow Labs, the leader in healthcare NLP, and Databricks are tackling these challenges head-on and working with many customers across the healthcare ecosystem to translate unstructured oncology data into actionable evidence.Clinical natural language processing at scale with Databricks & John Snow LabsThe path forward begins with the Databricks Lakehouse Platform, a modern data platform that combines the best elements of a data warehouse—such as data management and performance —with the low cost, flexibility and scale of a cloud data lake. This new, simplified architecture enables health systems to unify all their data—structured (e.g. diagnoses and procedure codes found in EHR databases), semi-structured (e.g. HL7, FHIR messages) and unstructured (e.g. free-text notes and images)— into a single, high-performance platform for both traditional analytics and data science.At the core of the Databricks Lakehouse Platform is Delta Lake, an open-source storage layer that brings performance (via Apache Spark™), reliability and governance to a data lake. Healthcare organizations can land all of their data – including raw provider notes, radiology reports and PDF pathology reports – into Delta Lake. This preserves the original source of truth before applying any data transformations. By contrast, with a traditional data warehouse, transformations occur prior to loading the data, which means that all structured variables extracted from unstructured text are disconnected from the native text.Building on this foundation is John Snow Labs' Spark NLP for Healthcare, the most widely-used NLP library in the healthcare and life science industries. Optimized to run on Databricks, Spark NLP for Healthcare seamlessly extracts, classifies and structures clinical and biomedical text data with state-of-the-art accuracy at scale. It is the only native distributed open-source text processing library for Python, Java and Scala, and since every Spark NLP pipeline is a Spark ML pipeline, it is particularly well suited to building unified NLP and machine learning pipelines. Spark NLP provides Python, Java and Scala libraries with the full functionality of traditional NLP libraries (like spaCy, nltk, Stanford CoreNLP and Open NLP) and adds additional functionality, such as spell-checking, sentiment analysis and document classification. You can learn more about the joint Databricks and John Snow Labs solution in our previous blog, Applying Natural Language Processing to Health Text at Scale.Real-world oncology data abstraction in actionTo demonstrate the power of Databricks and John Snow Labs, we created a Solution Accelerator for abstracting real-world data from oncology notes. The solution accelerator contains sample data, prebuilt code and step-by-step instructions for ingesting and preparing oncology reports for downstream analytics and real-world evidence generation. The solution is ready to go in a Databricks notebook and to help you get started, we've included a brief walkthrough of the solution below.For this solution we used the MT ONCOLOGY NOTES dataset. It offers resources primarily in the form of transcribed sample medical reports across medical specialties and common medical transcription words/phrases encountered in specific sections that form part of a medical report – sections such as physical examination or PE, review of systems or ROS, laboratory data and mental status exam, among others.We chose 50 de-identified oncology reports from the MT Oncology notes dataset as the source of the unstructured text and landed the raw text data into the Delta Lake bronze layer. For demonstration purposes, we limited the number of samples to 50, but the framework presented in this solution accelerator can be scaled to accommodate millions of clinical notes and text files.The first step in our accelerator is to extract variables using various models for Named-Entity Recognition (NER). To do that, we first set up our NLP pipeline, which contains annotators such as documentAssembler and sentenceDetector and tokenizer that are trained specifically for healthcare-related NER. In the example below, we combined bionlp_ner, which is a clinical NER model, and jsl_ner, which is a pre-trained deep NER model for clinical terminology. We see that the mesothelioma patient is experiencing symptoms such as coughing.Extracting named entities from texts is a great example of AI-assisted ETL: pre-trained deep learning (DL) models enable us to transform unstructured data into a structured format that can be used for downstream clinical analysis.Once we have the symptoms extracted, we can map to ICD-10 codes, which can be used for coding automation and improving Hierarchical Condition Category (HCC) coding accuracy for Medicare Risk Adjustment. We can further use this data to analyze treatment patterns and analyze the association between symptoms and oncological entities.Figure 1: Average risk indication for coded symptoms in the clinical datasetFigure 2: A visualization of symptom enrichment among most frequent conditions in the datasetWe can also generate a chart to study the assertion status of these symptoms as being present, absent or associated with someone else (for example, a family member).Continuing with the same note set, we run descriptive and visual statistics to display the most common oncology entities (example below) stratified by their assertion status.Figure 3: Assertion Status Of Most Common Symptoms.Next, we can look at treatments, including drug frequency and duration, which form the basis of oncology regimens. Below is a screenshot of the NLP model included in our solution notebook extracting drug treatment and duration information.We can then associate symptoms in relation to treatments, as well as disease statuses such as relapse, with confidence scores.This data is critical for ensuring both the quality of individual patient care and population-level research, which can help determine the efficacy and safety of interventions in the real world.Using the Databricks Lakehouse Platform, we can also easily create a database of conditions, symptoms and procedures, along with other relevant extracted information from the unstructured notes, which can then be used for downstream analysis, clinical decision support and research.With this solution accelerator, Databricks and John Snow Labs have opened the door to extract oncology data at scale with the quality required for real-world evidence generation.Get started extracting RWD from oncology notes with NLPTo use this solution, preview the notebooks online or get started right away by downloading and importing the notebooks into your Databricks account. The notebooks include guidance for installing the related John Snow Labs NLP libraries and license keys.You can also visit our industry pages to learn more about our Healthcare and Life Sciences solutions.Try Databricks for freeGet StartedSee 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
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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
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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
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https://www.databricks.com/dataaisummit/speaker/thet-ko
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Thet Ko - 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 ExperiencePricingThet KoPrincipal Data Engineer at SEEKBack to speakersThet Ko has 10+ years experience working across the full stack from cloud infrastructure, databases, backend systems to front end development. He is currently a Principal Engineer at SEEK responsible for supporting over 165 engineers and scientists scale their analysis on 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.
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https://www.databricks.com/dataaisummit/speaker/jun-rong-lau
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Jun Rong Lau - 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 ExperiencePricingJun Rong LauData Engineer/Analyst at GrabTaxi Holding Pte LtdBack to speakersFrom the Analytics Data Platform and Finance Data + AI transformation TeamLooking 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/dataaisummit/speaker/danica-fine
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Danica Fine - 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 ExperiencePricingDanica FineSenior Developer Advocate at ConfluentBack to speakersDanica Fine is a Senior Developer Advocate at Confluent where she helps others get the most out of their event-driven pipelines. In her previous role as a software engineer on a streaming infrastructure team, she predominantly worked on Kafka Streams- and Kafka Connect-based projects. She can be found on Twitter, tweeting about tech, plants, and baking @TheDanicaFine.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/dataaisummit/speaker/matthew-hayes-0
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Matthew Hayes - 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 HayesSoftware Engineer 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.
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https://www.databricks.com/explore/de-data-warehousing/a-new-approach-to-data-sharing
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A New Approach To Data Sharing
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https://www.databricks.com/kr/product/data-lakehouse
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Databricks의 데이터 레이크하우스 플랫폼 - 지금 데모를 예약하세요! | DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센 터웨비나 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 레이크하우스 플랫폼데이터 웨어하우징 및 AI 사용 사례를 하나의 플랫폼에 통합무료 시험판사용해 보기
WEBINAR • Goodbye, Data Warehouse. Hello, Lakehouse.
Attend on May 18 and get a $100 credit toward a Databricks certification course
Register now단순한 오픈 멀티클라우드Databricks 레이크하우스 플랫폼은 데이터 레이크와 데이터 웨어하우스의 장점만을 결합하여 데이터 웨어하우스의 안정성, 강력한 거버넌스, 성능을 제공하면서도 데이터 레이크의 개방성, 유연성, 머신 러닝 기능을 지원합니다.이러한 통합적 접근법은 지금까지 데이터 엔지니어링, 분석, BI, 데이터 사이언스, 머신 러닝을 구분하고 복잡하게 하던 데이터 사일로를 제거하여 현대적 데이터 스택을 간소화합니다. 오픈 소스와 개방형 표준 기반으로 구축하여 유연성을 극대화합니다. 데이터 관리, 보안 및 데이터 거버넌스에 공통적 방식을 적용함으로써, 효율은 향상하고 혁신은 높이는 효과를 제공합니다.심플이 통합적 접근법은 기존에 분석, 데이터 과학과 머신 러닝을 구분하던 데이터 사일로를 없애 데이터 아키텍처를 간소화합니다. 레이크하우스를 사용하면 분석과 AI 이니셔티브의 모든 잠재력을 실현하는 데 방해가 되는 복잡성과 비용 문제를 해결할 수 있습니다.오픈Delta Lake는 데이터 레이크에 저장된 데이터에 직접 안정성과 세계 최고 수준의 성능을 제공하여 레이크하우스의 오픈형 기반을 구성합니다. 배타적으로 구획을 구분할 필요 없이 데이터를 간편하게 공유하고, 오픈 소스 데이터 프로젝트와 광범위한 Databricks 파트너 네트워크로 구성된 에코시스템에 언제든 액세스하여 현대적 데이터 스택을 구축할 수 있습니다.데이터 환경 전반의 450+ 파트너에 대해 자세히 알아보기더 알아보세요멀티클라우드Databricks 레이크하우스 플랫폼은 모든 클라우드에 일관적인 관리, 보안 및 거버넌스 환경을 제공합니다. 사용하던 모든 클라우드 플랫폼에 대한 프로세스를 새롭게 개발하지 않아도 데이터와 AI 활동을 지원할 수 있습니다. 그 대신 데이터팀은 모든 데이터 작업을 새로운 인사이트를 발견하는 데 집중할 수 있습니다.더 알아보세요데이터와 데이터 팀의 잠재력 활용Databricks 레이크하우스 플랫폼이 데이터 및 AI 워크로드를 지원하는 방법에 대해 자세히 알아보기Data engineeringDatabricks SQL머신 러닝관련 콘텐츠
여러분에게 필요한 모든 리소스가 한 곳에 있습니다.
리소스 라이브러리의 ebook과 동영상을 통해 Databricks에서 데이터 엔지니어링을 활용하는 장점에 대해 알아보세요.
리소스 둘러보기레이크하우스레이크하우스란 무엇입니까?초보자를 위한 개론서: 최신 클라우드 데이터 플랫폼레이크하우스 패러다임의 부상데이터 레이크하우스의 부상 by 빌 인몬, 데이터 웨어하우스의 아버지Delta Lake데이터 엔지니어링 Big BookDelta Lake: 완전 정복 가이드(글: O’Reilly)Delta Lake 완전 정복 가이드Delta Lake: 레이크하우스의 기초머신 러닝eBook: ML 수명 주기 표준화가상 이벤트: 머신 러닝 플랫폼 빌드시작할 준비가 되셨나요?Databricks 무료로 시작하기제품플랫폼 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.
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https://www.databricks.com/trust/privacy
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Security and Trust Center - 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
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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 NOWSecurity & Trust CenterYour data security is our priority
OverviewTrustSecurity FeaturesArchitectureCompliancePrivacyReport an IssueOverview
Databricks takes privacy seriously. We understand that the data you analyze using Databricks is important both to your organization and your customers, and may be subject to a variety of privacy laws and regulations.
To help you understand how Databricks fits into regulatory frameworks that may apply to you, we’ve prepared Privacy FAQs and documents that transparently set forth how Databricks approaches privacy.ResourcesPrivacy PolicyPrivacy FAQsDatabricks SubprocessorsData Processing AddendumSecurity AddendumProductPlatform 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.
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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/dataaisummit/speaker/lindsey-woodland
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Lindsey Woodland - 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 ExperiencePricingLindsey WoodlandExecutive Vice President, Client Data Science at 605Back 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.
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https://www.databricks.com/dataaisummit/speaker/chunxu-tang
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Chunxu Tang - 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 ExperiencePricingChunxu TangResearch Scientist at AlluxioBack to speakersDr. Chunxu Tang is a Research Scientist at Alluxio and a committer of PrestoDB. Prior to Alluxio, he served as a Senior Software Engineer in Twitter’s data platform team, where he gained extensive experience with a wide range of data systems, including Presto, Zeppelin, BigQuery, and Druid. He received his Ph.D. from Syracuse University, where he conducted research on distributed collaboration systems and machine learning applications.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/dataaisummit/speaker/zachary-huang
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Zachary Huang - 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 ExperiencePricingZachary HuangPhD at Columbia UniversityBack to speakersZachary Huang is a PhD student at Columbia University. His research interests are in novel data management systems over large join graphs. His research works have been applied to data exploration, machine learning, and data market.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/dataaisummit/speaker/austin-ford
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Austin Ford - 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 ExperiencePricingAustin FordStaff Product Manager at DatabricksBack to speakersAustin is a product leader and former mathematician from Columbus, Mississippi. He is currently a Sr. Product Manager at Databricks in San Francisco and is responsible for the Databricks Notebook and the data science development experience in 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.
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https://www.databricks.com/session_na20/rapid-response-to-hospital-operations-using-data-and-ai-during-covid-19
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Beacons Hub Page | 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 Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing – all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark™, Delta Lake, MLflow and others. Don’t hesitate to reach out to them on social to see what they’re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.
UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark™ committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark™, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark™ adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark™.POLANDMaciej SzymkiewiczMaciej is an Apache Spark™ committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark™ committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark™, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select
Databricks eventsSponsorship and swag for meetupsNominate a peerWe’d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone — including customers, partners, Databricks employees or even a current Beacon — is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform 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
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Events Policy - 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 ExperiencePricingEvents PolicyPaymentsIn-person conference tickets and both in-person and virtual training will be assessed a fee and must be purchased with a credit card. Payment will be accepted in US dollars only. All registration fees must be paid in full prior to attending the conference. You will receive a payment confirmation and receipt via email once your credit card is processed and payment is complete. In order to receive the prices listed online you must complete and submit the online registration form by midnight (PST) on the deadline date. Any registration completed online after midnight (PST) will be processed at the next deadline price.
Promo CodesIf you have a promo code, you must apply it at the time of your registration. Only one (1) promo code can be applied per registration.
Transfers, Cancellation, and RefundsSubstitutions/Registration Transfer
Substitution requests can be processed in person onsite or via written request at [email protected] 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 p.m. (Pacific) 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 via email at [email protected] by June 21, 2023.
Payment Information
Payment accepted in US dollars only.
Refunds
All paid items (such as training or in person registration packages) will be refunded to the original form of payment.
We will issue a full refund, less a 10% fee, for written cancellation requests received on or before March 27, 2023 at 11:59 PM PT. Cancellation requests received between March 28, 2023 and May 25, 2023 at 11:59 PM PT, will be issued a 50% refund, less 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 Databricks Registration Team at [email protected]
Please note: Any requests to change the payment method used for a completed registration will incur a $50 change fee. If you need to make a change, please contact the Databricks Registration Team at: [email protected] Databricks reserves the right to deny registration to any individual or entity for any reason, in Databricks’s sole discretion, including for past or present failure to meet Databricks’s standards of conduct (including, but not limited to, engaging in violent, illegal, threatening, or discriminatory conduct). Payment terms are Net 30. Payment must be received in full to print attendee badge on-site.
Registration ConfirmationRegistration will be confirmed by email. You’ll receive a message as soon as payment has been received and your registration has been processed.
Speakers & SessionsThe speakers listed on this website are leading professionals in their respective fields. Should a speaker be unable to attend the conference, all efforts will be made to replace him or her with one of comparable experience and qualifications. We are constantly working on improving the quality of our conference products. If the opportunity arises we may, at our discretion, add conference sessions and workshops to the posted line-up to enhance the schedule.
Photo Release & Privacy InformationFrom time to time Databricks may choose to photograph and record certain portions of the conference and may capture conference participants. Databricks may choose such photographs and recordings in our promotional materials. By virtue of your attendance at Data + AI Summit you consent to, Databricks’ use of your likeness in such materials and you hereby waive “moral rights” in such photos, recordings, or other digital content. You agree that any personal data you provide us will be handled in accordance with this Event Policy and our Privacy Policy.
You may not record any sessions or sessions at Data + AI Summit without prior approval from Databricks.
Terms of Use. Privacy Policy. Code of Conduct.
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.
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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
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https://www.databricks.com/company/partners/consulting-and-si/partner-solutions/avanade-cpg-control-tower
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CPG Control Tower by Avanade | 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 NOWBrickbuilder SolutionCPG Control Tower by AvanadeIndustry-specific solution developed by Avanade and powered by the Databricks Lakehouse PlatformGet startedGet control of your supply chainCustomer needs are shifting faster than ever before, and organizations in the consumer packaged goods (CPG) industry need better insights to outpace change across their business. Avanade’s solution, the CPG Control Tower, gives you unprecedented oversight of your supply chain and manufacturing operations. The solution can help you find valuable insights through a direct view of the data impacting your business, empowering smarter business decisions surrounding financial performance, operational excellence, risk and more. Use the Control Tower to produce a resilient, profitable and customer-centric supply chain.Ability to model scenarios and impact on supply chain 2–3x fasterReduction in idle “trapped” cash, adjusted use of credit lines, reduction of bank fees, and a more concentrated cash positionAvanade clients using CPG Control Tower have seen a greater than 10% return on investment as well as a 10%–12% sales increaseGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases. See our full library of solutions ➞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
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Azure Databricks - Unifica tutti i carichi di lavoro di analisi e AI | 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 NOWAzure DatabricksServizi di gestione dei dati e AI di Databricks, forniti attraverso Microsoft Azure, per conservare tutti i dati su un semplice lakehouse aperto e per unificare tutti i carichi di lavoro di analisi e AI.CominciaProgramma una demoAzure Databricks è ottimizzato per Azure e strettamente integrato con Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Power BI e altri servizi Azure per conservare tutti i dati su un semplice lakehouse aperto e unificare tutti i carichi di lavoro di analisi e AI.Semplice
Unifica dati, analisi e AI
su una piattaforma comune per tutti i casi di utilizzo dei datiAperta
Unifica l'ecosistema di dati
con open source, standard e formatiCollaborativa
Unifica i team di dati
per collaborare lungo tutto il flusso di lavoro di gestione dei dati e AIPerché Azure DatabricksPrestazioni 50 volte superiori per carichi di lavoro Apache Spark™
Implementa cluster di calcolo auto-scalabili con Spark altamente ottimizzato che offrono prestazioni fino a 50 volte più veloci.Maggiori informazioniMilioni di ore-server al giorno
Azure Databricks ha conquistato la fiducia di migliaia di clienti che ogni giorno eseguono milioni di ore di lavoro sui server in oltre 34 regioni Azure.Maggiori informazioniFacilità d'uso
Comincia con un solo clic nel portale di Azure, effettua l'integrazione nativa con i servizi di sicurezza e dati di Azure e aumenta la produttività fino al 25% grazie ad attività collaborative di data engineering e data science.Maggiori informazioniCasi d'uso per settoreServizi finanziariSwiss Re
Analisi dei dati unificata per data engineering, data science e analisti.HSBC
Ha costruito una piattaforma di pagamento digitale utilizzando Azure Databricks.ABN AMROHa migliorato i flussi di lavoro di analisi grazie a collaborazione, approfondimenti AI e funzionalità avanzate di machine learning automatizzato.Maggiori informazioniretailSanità e bioscienzePartecipa a un evento Azure DatabricksDatabricks, Microsoft e i rispettivi partner sono entusiasti di ospitare questi eventi dedicati ad Azure Databricks. Unisciti a noi partecipando a un evento nella tua zona per conoscere meglio il servizio Dati + AI che cresce più velocemente su Azure! Il programma e il formato sono diversi per ogni evento, consulta la pagina dedicata per conoscere tutti i dettagli. Maggiori informazioniOttimizzato per AzureIntegrazione diretta con data store e servizi di Azure tramite connettori specifici, per un accesso veloce ai dati e una gestione semplificata in tutto l'ambiente. Con questo approccio risulta facile impostare i controlli di sicurezza, gestire gli ambienti ed elaborare tutti i dati su Azure.Maggiori informazioniIntegrazioni disponibiliAzure Active DirectorySingle Sign-On (accesso unico) con Azure Active Directory è il modo migliore per accedere ad Azure Databricks. Azure Databricks supporta anche il provisioning automatizzato degli utenti con Azure AD per creare nuovi utenti, fornire loro il livello di accesso appropriato ed eliminare utenti per disabilitare l'accesso.Azure Data Lake StorageAzure Data FactoryAzure Synapse AnalyticsPower BIAzure DevOpsAzure Virtual NetworkAzure Event HubsAzure Key VaultRisorseWhitepaperAzure Databricks per data engineeringAzure Databricks: la piattaforma migliore per ML e AITre casi d'uso pratici con Azure DatabricksPrimi passi con Apache Spark su Azure DatabricksVideoAli Ghodsi e Rohan Kumar (CVP, Microsoft), conversazione davanti al caminetto al Keynote Data + AI Summit NA 2021Demo integrazione in cloud di Databricks su AzureIngestione di dati in Delta Lake su Azure DatabricksEsplorazione di dati con Databricks SQLeBookGartner Magic Quadrant 2021 per piattaforme di data science e machine learningPiattaforme moderne per la gestione di dati in cloud per principianti8 passi per gli sviluppatori che vogliono imparare a usare Apache Spark™ con Delta LakeApache Spark™ visto da dentro: introduzione all'architettura e ai concetti chiavePronto per cominciare?CominciaProgramma 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. 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
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https://www.databricks.com/dataaisummit/speaker/stefania-leone
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Stefania Leone - 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 ExperiencePricingStefania LeoneSr. Manager Product Management at DatabricksBack to speakersStefania is a product manager at Databricks working on the Databricks Runtime. She holds a PhD in Computer Science from ETH Zurich.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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Corey Zumar - 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 ExperiencePricingCorey ZumarSoftware Engineer at DatabricksBack to speakersCorey has been working as a Software Engineer at Databricks for the last 4 years and has been an active contributor to and maintainer of MLflow since its first release.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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Hari Shankar - 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 ExperiencePricingHari ShankarSenior Director, R&D at VizioBack to speakersHari Shankar is the Senior Director of R&D, Data Engineering, for Vizio, the connected home and entertainment leader. At Vizio, Hari was responsible for leading their Databricks and lakehouse migration, as well as managing their AdTech platform strategy. Prior to Vizio, Hari worked at Samsung, NetApp, and Sun Microsystems in technical leadership 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.
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https://www.databricks.com/dataaisummit/speaker/ioannis-papadopoulos/#
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Ioannis Papadopoulos - 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 ExperiencePricingIoannis PapadopoulosCloud Technologist at DatabricksBack to speakersIoannis is a Cloud Technologist at Databricks, working in collaboration with the technical fields of AWS, Azure, and GCP.
He started his career at CERN as a research physicist and then moved to Apple to lead the business development of the research markets in EMEA.
Before joining Databricks, Ioannis had co-founded 3 startups, where he championed the development of serverless architectures on the cloud.
Ioannis holds a Ph.D. in Physics, an MBA, and an Executive Master in digital transformation.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/it/solutions/industries/retail-industry-solutions
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La soluzione di data lakehouse per commercio al dettaglio e largo consumo - 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 NOWScopri Lakehouse for RetailLa piattaforma unificata per dati, analisi e AI utilizzata dalle aziende retail per ottimizzare l'offerta in ogni fase del percorso del clienteRegistratiContattiPrestazioni migliori, portata più ampia, costi di gestione (TCO) minoriLakehouse per il retailUnifica i carichi di lavoro di dati e AI con condivisione e governance integrate, in modo che i team interni ed esterni abbiano accesso ai dati di cui hanno bisogno, quando ne hanno bisognoImpatto su tutta la catena del valoreCoinvolgimento del clientePertinenza e iper-personalizzazione in ogni punto di contattoGrazie a viste dei clienti a 360°, precise e in tempo reale, le aziende di commercio al dettaglio hanno tutto ciò che serve per instaurare relazioni personalizzate con ciascun cliente, grazie alla capacità di intercettare il sentiment su tutti i canali e personalizzare le raccomandazioni. Risultato: maggiore redditività e fidelizzazione.Efficienza operativaProduttività dei dipendentiPrestazioni dei prodottiSoluzioni e partner nel settore retailSoluzioni di analisi dei dati e AI senza compromessi realizzate appositamente per il tuo settoreGli Acceleratori Databricks sono guide specifiche — notebook con funzionalità complete e best practice — che velocizzano il raggiungimento di risultati nel commercio al dettaglio. Risparmia tempo nelle attività di scoperta, progettazione, sviluppo e collaudo per casi d'uso come punteggi di propensione agli acquisti, valore del ciclo di vita del cliente (CLV), ottimizzazione del prelievo di ordini e altro ancora.Previsioni granulariGenerare previsioni su larga scala in meno tempo
Genera previsioni granulari a livello di singolo negozio-articolo in modo efficiente, sfruttando la potenza di calcolo distribuita della Databricks Lakehouse Platform.CominciaSegmentazione clientiSegmentare i clienti per indirizzare meglio le iniziative
Crea categorie di clienti avanzate utilizzando dati di vendita, campagne, sistemi promozionali e altri strumenti per migliorare le previsioni di acquisto in base ai comportamenti.CominciaAnalisi del punto vendita in tempo realeCalcolare in tempo reale gli inventari di molteplici negozi per migliorare i margini di guadagno nel commercio al dettaglio
Acquisisci rapidamente tutte le sorgenti e le tipologie di dati dei punti vendita, su larga scala, per ricavare dati approfonditi in tempo reale che soddisfano il fabbisogno pressante di informazioni sui negozi.CominciaScopri gli acceleratori per il commercio al dettaglioAbbiamo collaborato con le principali società di consulenza per fornire soluzioni innovative per settori specifici. Le soluzioni Databricks Brickbuilder aiutano a ridurre i costi e aumentare il valore generato dai dati. Con decenni di competenze settoriali alle spalle — e specificamente costruite per la Databricks Lakehouse Platform — le soluzioni Brickbuilder sono ritagliate su misura per le tue esigenze.Vista unificata della domandaMassimizzare la precisione, la granularità e la puntualità con un piano della domanda che attinge a un'unica "fonte della verità".Maggiori informazioniGestione della crescita dei ricaviEseguire rapidamente l'analisi di dati di fatturazione, dati di mercato esterni, notizie e web scraping (estrazione di dati da siti web) per analizzare modalità e schemi ricorrenti del commercio al dettaglio.Maggiori informazioniTrellisRisolvere problematiche di previsione della domanda, rifornimenti, approvvigionamenti, prezzi e servizi promozionali.Maggiori informazioniScopri le soluzioni Brickbuilder“Ora riusciamo a combinare, per ogni singolo cliente, le informazioni sugli acquisti online e offline, un'attività che in passato era molto complessa. Questa vista omnicanale ci consente di creare un motore di raccomandazioni online più completo, che favorisce un notevole coinvolgimento”.
— Wendell Kuling, Manager of Data Science and Analytics, Jumbo
“Databricks ci consente di avere le prestazioni migliori e offrire al cliente esperienze best-in-class in ogni settore. Grazie alla Lakehouse Platform, i nostri responsabili e sviluppatori possono lavorare in modo più collaborativo, individuando le tendenze principali e acquisendo le informazioni approfondite e dettagliate necessarie per servire i nostri oltre 180 milioni di clienti”.
— Sergiy Tkachuk, Head of Data Science, Reckitt
Sempre più reparti utilizzano la piattaforma con una modalità self-service che in passato non era possibile. Non esistono parole adeguate per descrivere l'impatto positivo di Databricks su Columbia”.
— Lara Minor, Senior Enterprise Data Manager, Columbia Sportswear
RisorseTour autoguidatoTutte le risorse di cui hai bisogno per conoscere Lakehouse for RetailWebinarPrendere decisioni in tempo reale nel commercio al dettaglioeBookIl grande libro dei casi d'uso nel commercio al dettaglioProdottoPanoramica 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
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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. 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/customers/hp-inc
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Customer Case Study: HP, Inc. | 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 STORYReal-time IoT device management at scale Vertical Use Case: IoT,Real-time device management,Process optimization Technical Use Case: Ingest/ETL,Machine Learning"Databricks’ unified platform has helped foster collaboration across our data science and engineering teams which has impacted innovation and productivity."
— John Landry, Distinguished Technologist at HP, Inc.HP Inc. was created in 2015 when Hewlett-Packard was split into two separate companies, HP Enterprise, and HP Inc. HP Inc. creates technology that makes life better for everyone, everywhere. Through a portfolio of printers, PCs, mobile devices, solutions, and services, their stated mission is to engineer experiences that amaze.The ChallengesSiloed data: Data stored in multiple systems, in multiple places, that was hard to access and analyzeExisting tools difficult to manage: Reliance on old data warehousing technologies and tooling resulting in heavy DevOps work, which typically fell on the data science teamThe SolutionDatabricks provides HP Inc. with a scalable, affordable, unified analytics platform that allows them to predict product issues and uncover new customer services:Simplified management of Apache Spark™: Turnkey unified platform removed infrastructure complexity and empowered the data scientists to focus on the data and not DevOpsAnalysis of high volume data in flight: Analyze data from more than 20 million devices with a seamless workflowImproved collaboration and productivity: a unified platform for business analysts, data scientists, and subject matter expertsReady 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.
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https://www.databricks.com/dataaisummit/speaker/daniela-rus/#
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Daniela Rus - 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 ExperiencePricingDaniela RusProfessor of EECS and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MITBack to speakersDaniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. Rus’s research interests are in robotics, mobile computing, and data science. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, and a member of the National Academy of Engineering, and the American Academy for Arts and Science. She earned her PhD in Computer Science from Cornell 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.
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https://www.databricks.com/dataaisummit/speaker/chris-vo
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Chris Vo - 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 ExperiencePricingChris VoLead Member of Tech Staff at AT&TBack to speakersChris Vo has 25+ years of software development experience. He has multiple Azure and Databricks certifications. He earned a Master's Degree in Computer Science at the University of Texas at Dallas (UTD) and a Bachelor's Degree in Computer Science at the University of Texas at Arlington (UTA).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/dataaisummit/speaker/hyukjin-kwon/#
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Hyukjin Kwon - 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 ExperiencePricingHyukjin KwonStaff Software Engineer at DatabricksBack to speakersHyukjin is a Databricks software engineer as the tech-lead in OSS PySpark team, Apache Spark PMC member and committer, working on many different areas in Apache Spark such as PySpark, Spark SQL, SparkR, infrastructure, etc. He is the top contributor in Apache Spark, and leads efforts such as Project Zen, Pandas API on Spark, and Python Spark Connect.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/dataaisummit/speaker/geoffrey-freeman
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Geoffrey Freeman - 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 ExperiencePricingGeoffrey FreemanSolutions Architect at T-MobileBack to speakersGeoffrey Freeman has spent most of his career working in massive scale online data delivery services. He is currently a solution architect for T-Mobile's procurement division.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/dataaisummit/speaker/aman-kapoor
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Aman Kapoor - 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 ExperiencePricingAman KapoorHead of Data Platform at PetronasBack 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.
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https://www.databricks.com/dataaisummit/speaker/arthur-li
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Arthur Li - 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 ExperiencePricingArthur LiSenior Software Engineer at InstacartBack to speakersArthur Li is a software engineer who has been working at Instacart for the past two years focusing on batch data processing infrastructure. He has contributed to the company's data platform team by implementing data collection and management strategies that have streamlined the company's data infrastructure.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/glossary/extract-transform-load
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What is ETL?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 NOWExtract Transform Load (ETL)All>Extract Transform Load (ETL)What is ETL?As the amount of data, data sources, and data types at organizations grow, the importance of making use of that data in analytics, data science and machine learning initiatives to derive business insights grows as well. The need to prioritize these initiatives puts increasing pressure on the data engineering teams because processing the raw, messy data into clean, fresh, reliable data is a critical step before these initiatives can be pursued. ETL, which stands for extract, transform, and load, is the process data engineers use to extract data from different sources, transform the data into a usable and trusted resource, and load that data into the systems end-users can access and use downstream to solve business problems.How Does ETL Work?ExtractThe first step of this process is extracting data from the target sources that are usually heterogeneous such as business systems, APIs, sensor data, marketing tools, and transaction databases, and others. As you can see, some of these data types are likely to be the structured outputs of widely used systems, while others are semi-structured JSON server logs.There are different ways to perform the extraction: Three Data Extraction methods:Partial Extraction – The easiest way to obtain the data is if the if the source system notifies you when a record has been changedPartial Extraction (with update notification) - Not all systems can provide a notification in case an update has taken place; however, they can point to those records that have been changed and provide an extract of such records.Full extract – There are certain systems that cannot identify which data has been changed at all. In this case, a full extract is the only possibility to extract the data out of the system. This method requires having a copy of the last extract in the same format so you can identify the changes that have been made.TransformThe second step consists of transforming the raw data that has been extracted from the sources into a format that can be used by different applications. In this stage, data gets cleansed, mapped and transformed, often to a specific schema, so it meets operational needs. This process entails several types of transformation that ensure the quality and integrity of data Data is not usually loaded directly into the target data source, but instead it is common to have it uploaded into a staging database. This step ensures a quick roll back in case something does not go as planned. During this stage, you have the possibility to generate audit reports for regulatory compliance, or diagnose and repair any data issues.LoadFinally, the load function is the process of writing converted data from a staging area to a target database, which may or may not have previously existed. Depending on the requirements of the application, this process may be either quite simple or intricate. Each of these steps can be done with ETL tools or custom code.What is an ETL pipeline?An ETL pipeline (or data pipeline) is the mechanism by which ETL processes occur. Data pipelines are a set of tools and activities for moving data from one system with its method of data storage and processing to another system in which it can be stored and managed differently. Moreover, pipelines allow for automatically getting information from many disparate sources, then transforming and consolidating it in one high-performing data storage.Challenges with ETLWhile ETL is essential, with this exponential increase in data sources and types, building and maintaining reliable data pipelines has become one of the more challenging parts of data engineering. From the start, building pipelines that ensure data reliability is slow and difficult. Data pipelines are built with complex code and limited reusability. A pipeline built in one environment cannot be used in another, even if the underlying code is very similar, meaning data engineers are often the bottleneck and tasked with reinventing the wheel every time. Beyond pipeline development, managing data quality in increasingly complex pipeline architectures is difficult. Bad data is often allowed to flow through a pipeline undetected, devaluing the entire data set. To maintain quality and ensure reliable insights, data engineers are required to write extensive custom code to implement quality checks and validation at every step of the pipeline. Finally, as pipelines grow in scale and complexity, companies face increased operational load managing them which makes data reliability incredibly difficult to maintain. Data processing infrastructure has to be set up, scaled, restarted, patched, and updated - which translates to increased time and cost. Pipeline failures are difficult to identify and even more difficult to solve - due to lack of visibility and tooling. Regardless of all of these challenges, reliable ETL is an absolutely critical process for any business that hopes to be insights-driven. Without ETL tools that maintain a standard of data reliability, teams across the business are required to blindly make decisions without reliable metrics or reports. To continue to scale, data engineers need tools to streamline and democratize ETL, making the ETL lifecycle easier, and enabling data teams to build and leverage their own data pipelines in order to get to insights faster.Automate reliable ETL on Delta LakeDelta Live Tables (DLT) makes it easy to build and manage reliable data pipelines that deliver high quality data on Delta Lake. DLT helps data engineering teams simplify ETL development and management with declarative pipeline development, automatic testing, and deep visibility for monitoring and recovery.Additional ResourcesDelta Live Tables DemoDelta Lake: The Foundation of Your Lakehouse WebinarData Management: The Good The Bad The Ugly WebinarGetting Started with Delta Live TablesBack 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
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https://www.databricks.com/dataaisummit/speaker/tianyu-liu
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Tianyu Liu - 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 ExperiencePricingTianyu LiuLead Data Scientist (Analytics) at GrabBack to speakersFrom the Analytics Data Platform and Finance Data + AI Transformation Team at Grab.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/dataaisummit/pricing?itm_data=hp-hamburger-pricing-dais23
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Pricing - 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 ExperiencePricingPricingConference
Full Conference PassThe full conference pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.
$1795 IN-PERSON
Group DiscountGroups of 4 or more. Must be purchased in one transaction. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.
$1295 IN-PERSONEACH
GOV/EDU/NFPDiscounted pass for Government/Education/Non Profit Organization employees. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access.
$1395 IN-PERSON
Virtual ExperienceThe free virtual experience includes livestreamed keynotes and unlimited access to on-demand sessions following the event.
$0 VIRTUALTraining
Two-Day CourseThis includes a two-day course and the certification exam.
$1125 IN-PERSON
Full-Day TrainingA comprehensive training workshop including a deep dive into your chosen topic.
$750 IN-PERSON
Half-Day TrainingA 4-hour, in-depth session covering your chosen topic.
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$0 IN-PERSONChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at “birds of a feather” meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark™, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingDon’t miss this year’s event!Register 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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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
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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
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Sanjeev Kumar - 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 ExperiencePricingSanjeev KumarVice President, Data Analytics and AI at Gainwell TechnologiesBack 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.
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Data Engineering | 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 EngineeringDezenas de milhões de cargas de trabalho produtivas são executadas diariamente no DatabricksIntroduçãoAssista à demonstração
WEBINAR • Goodbye, Data Warehouse. Hello, Lakehouse.
Attend on May 18 and get a $100 credit toward a Databricks certification course
Register nowIngira e transforme facilmente dados em batch e streaming na Plataforma Databricks Lakehouse. Orquestre fluxos de trabalho de produção confiáveis enquanto a Databricks gerencia automaticamente sua infraestrutura em escala. Aumente a produtividade de suas equipes com testes de qualidade de dados integrados e suporte às melhores práticas de desenvolvimento de software.Unifique batch e streamingElimine silos em uma plataforma com uma API unificada para ingerir, transformar e processar dados em batch e streaming de forma incremental em escala.Foque em extrair valor dos dadosA Databricks gerencia automaticamente sua infraestrutura e os componentes operacionais de seus fluxos de trabalho de produção para que você possa se concentrar no valor, não nas ferramentas.Conecte suas ferramentas de escolhaUma Plataforma Lakehouse aberta para se conectar e usar suas ferramentas preferidas de engenharia de dados para ingestão de dados, ETL/ELT e orquestração.Conte com a Plataforma LakehouseA Plataforma Lakehouse fornece a melhor fundação para construir e compartilhar ativos de dados confiáveis que são governados centralmente, confiáveis e extremamente rápidos."A Databricks está se tornando o recurso completo para todo o nosso trabalho de ETL. Quanto mais trabalhamos com a Plataforma Lakehouse, mais fácil é para os usuários e administradores."— Hillevi Crognale, gerente de engenharia da YipitDataComo funciona?Ingestão simplificada de dadosProcessamento automatizado de ETLOrquestração confiável de fluxos de trabalhoMonitoramento e observabilidade de ponta a pontaMotor de processamento de dados de última geraçãoFundação de governança, confiabilidade e desempenhoIngestão simplificada de dadosConsuma dados em sua Plataforma Lakehouse e potencialize suas análises, IA e aplicações de streaming de um só lugar. O Auto Loader processa de forma incremental e automática os arquivos que chegam ao armazenamento de nuvem, sem a necessidade de gerenciar informações de estado, em jobs programados ou contínuos. Ele rastreia com eficiência novos arquivos (escalando para bilhões) sem ter que listá-los em um diretório e também pode inferir automaticamente o esquema dos dados de origem e evoluí-lo conforme as mudanças ao longo do tempo. O comando COPY INTO facilita para analistas operarem a ingestão de arquivos em batch para o Delta Lake com SQL."Vimos um aumento de 40% na produtividade da engenharia de dados - reduzindo o tempo que leva para desenvolver novas idéias de dias para minutos e aumentando a disponibilidade e a precisão de nossos dados."— Shaun Pearce, diretor de tecnologia, GoustoSaiba maisProcessamento automatizado de ETLUma vez ingeridos, os dados brutos precisam ser transformados para que fiquem prontos para análise e IA. A Databricks fornece poderosos recursos ETL para times de engenharia, ciência e análise de dados com Delta Live Tables (DLT). DLT é a primeira estrutura que utiliza uma abordagem declarativa simples para construir pipelines ETL e ML em batch ou streaming de dados, enquanto automatiza complexidades operacionais tais como gerenciamento de infraestrutura, orquestração de tarefas, tratamento e recuperação de erros, e otimização de desempenho. Com as DLTs, a equipe de engenharia também pode tratar seus dados como código e aplicar as melhores práticas de engenharia de software como testes, monitoramento e documentação para criar pipelines confiáveis em escala.Saiba maisOrquestração de fluxos de trabalho confiávelOs fluxos de trabalho Databricks são o serviço de orquestração totalmente gerenciado para todos os seus dados, análises e IA nativos da sua Plataforma Lakehouse. Organize cargas de trabalho diversas em todo o ciclo de vida, incluindo Delta Live Tables e Jobs para SQL, Spark, notebooks, dbt, modelos de ML e muito mais. A integração profunda com a Plataforma Lakehouse garante que você crie e execute cargas de trabalho de produção confiáveis em qualquer nuvem e, ao mesmo tempo, forneça monitoramento profundo e centralizado com simplicidade para usuários finais.“Nossa missão é transformar a forma como alimentamos o planeta. Nossos clientes do setor de energia precisam de dados, consultoria e pesquisas para alcançar essa transformação. O Databricks Workflows nos dá a velocidade e a flexibilidade para fornecer os insights de que nossos clientes precisam.”— Yanyan Wu, vice-presidente de dados, Wood MackenzieSaiba maisMonitoramento e observabilidade de ponta a pontaA Plataforma Lakehouse oferece visibilidade em todo o ciclo de vida de dados e IA para que equipes de engenharia de dados e de operações possam ver a integridade de seus fluxos de trabalho de produção em tempo real, gerenciar a qualidade dos dados e entender tendências históricas. Nos Fluxos de trabalho da Databricks, você pode acessar gráficos de fluxo de dados e painéis que rastreiam a integridade e o desempenho de seus jobs produção e pipelines de Delta Live Tables. Os logs de eventos também são expostos como tabelas do Delta Lake para que você possa monitorar e visualizar métricas de desempenho, qualidade dos dados e confiabilidade de qualquer ângulo.Motor de processamento de dados de última geraçãoA engenharia de dados da Databricks é alimentada pelo Photon, o motor de última geração compatível com as APIs do Apache Spark, oferecendo preço/desempenho recordes enquanto escala automaticamente para milhares de nós. O Spark Structured Streaming oferece uma API unificada para processamento em batch e stream, facilitando a adoção do streaming no lakehouse sem alterar o código ou aprender novas habilidades.Saiba maisGovernança, confiabilidade e desempenho de dados de última geraçãoA engenharia de dados na Databricks significa que você se beneficia dos componentes fundamentais da Plataforma Lakehouse — Unity Catalog e Delta Lake. Seus dados brutos são otimizados com o Delta Lake, um formato de armazenamento de código aberto que fornece confiabilidade por meio de transações ACID e tratamento escalável de metadados com desempenho extremamente rápido. Isso se combina com o Unity Catalog para oferecer uma governança granular para todos os seus dados e ativos de IA, simplificando a forma como você governa, com um modelo consistente para descobrir, acessar e compartilhar dados entre as nuvens. O Unity Catalog também fornece suporte nativo para Delta Sharing, o primeiro protocolo aberto da indústria para compartilhamento de dados fácil e seguro com outras organizações.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 DatabricksIntegraçõesOfereça o máximo de flexibilidade às suas equipes de dados — aproveite o Partner Connect e um ecossistema de parceiros de tecnologia para se integrar perfeitamente a ferramentas populares de engenharia de dados. Por exemplo, você pode ingerir dados críticos de negócios com o Fivetran, transformá-los no lugar com dbt e orquestrar seus pipelines com o Apache Airflow.Ingestão de dados e ETL+ qualquer outro cliente compatível com Apache Spark™História de clienteDescubra maisDelta LakeFluxos de trabalhoDelta Live TablesDelta SharingConteúdo relacionado
Todos os recursos de que você precisa. Reunidos em um só lugar.
Explore nossa biblioteca de recursos: você encontrará e-books e vídeos sobre os benefícios da data engineering no Databricks.
Explorar recursose-booksBuilding the Data Lakehouse, de Bill Inmon, pai do data warehouseData, Analytics and AI governanceGerenciamento de dados 101e-book: The Big Book of Data EngineeringExplore a nova solução de Delta SharingLivro para leigos: Migrating from a Data Warehouse to a Data LakehouseEventosGerencie a transformação de dados com Delta Live TablesSérie de webinars sobre ingestão de dados sem complicaçõesData + AI Summit 2022Modernize seu data warehouseBlogsAnunciando disponibilidade geral de Delta Live Tables (DLT) da DatabricksApresentando os fluxos de trabalho da DatabricksUma visão geral de todos os novos recursos estruturados de streaming desenvolvidos em 2021 para Databricks e Apache Spark10 recursos poderosos para simplificar o gerenciamento de dados semiestruturados no Databricks LakehouseTudo pronto para começar?Experimente gratuitamenteJunte-se à comunidadeAWSAzureGCPProdutoVisão 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.
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Murali Madireddi - 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 ExperiencePricingMurali MadireddiArchitect at AccentureBack to speakersMurali is an accomplished architect with strong expertise in ETL, DW and Data lakes.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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Teja Tangeda - 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 ExperiencePricingTeja TangedaPrincipal Data Engineer at American AirlinesBack to speakersTeja Tangeda is a Principal Data Engineer at American Airlines. He has over a decade of experience as a Data Engineer. His love for aviation, travel, and data led him to American Airlines. Teja enjoys using his skills to solve complex data issues. He is inspired daily by his wife and two kids. In his free time, Teja likes to garden and take long walks.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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Mohan Kolli - 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 ExperiencePricingMohan KolliIT Director at LabCorpBack to speakersIT professional with 23 years of experience as Application Developer, Data Engineer, Data Architect, Data Warehouse lead and leadership roles. Currently working as Director of Enterprise Analytics Platform with portfolio of Data Platform, Data Modeling, Data Integration, Data Engineering and Data Governance. I am the visionary in data engineering and data platform space to develop data driven organization(s) to empower users make decision(s) timely with high confidence.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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