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https://www.databricks.com/dataaisummit/speaker/ryan-harris/#
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Ryan Harris - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRyan HarrisPrincipal Cybersecurity Engineer at HSBCBack to speakersRyan Harris is a Principal Cybersecurity Engineer on the Global Cybersecurity Science & Analytics Team at HSBC, focusing on transforming cybersecurity into a data-driven organization by designing and building a secure cloud-native environment to analyze petabytes of security data. For over 20 years he has leveraged data to disrupt financial services threat actors, preventing $100M+ in fraud. He served as a Captain in the USAF, and has a degree in Cognitive Science & Computer Science from UVa.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/fr/dataaisummit/?itm_data=menu-learn-dais23
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Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI.
Register NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you’re an engineering wizard, ML pro, SQL expert — or you want to learn how to build, train and deploy LLMs — you’ll be in good company.
See all 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, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI — and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer.
SessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more.
Explore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark™, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto/Trino, DuckDB and much more. You’ll also get a first look at new products and features in the Databricks Lakehouse Platform.
Browse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party.
Learn moreChoose 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 pricingTrusted by the data communityHear data practitioners from trusted companies all over the world
See agendaDon’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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https://www.databricks.com/dataaisummit/speaker/sidharth-kunnath/#
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Sidharth Kunnath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSidharth KunnathPrincipal Architect at American Airlines, IncBack to speakersOver 18 years of IT experience exclusively in designing and building enterprise data analytical solutions deployed over enterprise data warehouses and data lakes, both within on-premises and cloud (Azure)
Over 4 years of experience implementing data analytics projects within Azure data analytical ecosystem, leveraging Azure services like Event Hub (AEH), Stream Analytics (ASA), Azure Functions (AF), Databricks (ADB) and Azure Datalake Storage (ADLS)
Experience in defining enterprise data strategy and its physical implementation across the organization
Experience in Application, Solution and Data Architecture, working both with technology and the business, translating between the two
Experience in implementation of real-time data streaming layer using Azure streaming architecture as well as real-time data serving layer using APIs installed over NoSQL databases like Cassandra
Extensive experience implementing data warehousing projects based on Teradata
Domain knowledge of airline business including subject areas like revenue management & performance, customer loyalty, flight operations, inventory, maintenance & engineering.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
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https://www.databricks.com/dataaisummit/speaker/lee-yang/#
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Lee Yang - 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 ExperiencePricingLee YangSr. Principal SW Engineer at NVIDIABack to speakersLee Yang is a Sr. Principal Software Engineer at NVIDIA, working on integrating deep learning with Apache Spark. Before that, at Yahoo, he created and open-sourced TensorFlowOnSpark, a framework for large-scale, distributed TensorFlow training and inference using Spark.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/jp/company/about-us
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Databricks 企業概要 ― Apache Spark™ の開発者グループにより創業Skip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT
さようなら、データウェアハウス。こんにちは、レイクハウス。
データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。
今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)
製造業のためのレイクハウスを発見する
コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日
直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOWDatabricks は lakehouse 会社データブリックスは、学術界とオープンソースコミュニティに端を発し、Apache Spark™、Delta Lake、MLflow の開発者グループによって 2013 年に創業しました。クラウド上のレイクハウスプラットフォームとして世界初、世界唯一の、データウェアハウスとデータレイク両方の優れた特長を備えたデータと AI のためのオープンな統合プラットフォームを提供しています。
レイクハウスプラットフォームについて詳しく見る顧客数 7,000 社以上
ABN、AMRO、コンデナスト、H&M グループ、リジェネロン、シェルなど、世界中の 7,000 社以上の多様な業界のお客様がデータブリックスを利用し、大規模なデータエンジニアリング、コラボレーション型データサイエンス、ライフサイクル全体の機械学習、ビジネスアナリティクスを実現しています。
グローバルに展開
データブリックスは、本拠点のサンフランシスコおよび世界中に事業所を配し、さらに、Microsoft、Amazon、Tableau、Informatica、Cap Gemini、Booz Allen Hamilton などを含む数百におよぶパートナーと連携し、グローバルに事業を展開しています。データブリックスは、データと AI の簡素化と民主化をミッションに、データ活用によって難題解決に挑む組織の支援に取り組んでいます。導入事例を見るパートナーについて詳しく見るデータブリックスのお客様導入事例一覧へ
データブリックスの経営陣経営陣経営陣創業者創業者取締役取締役投資企業製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ 採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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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.プライバシー通知|利用規約|プライバシー設定|カリフォルニア州のプライバシー権利
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https://www.databricks.com/customers
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Databricks Customer Stories | 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 CustomersDiscover how innovative companies across every industry are leveraging the Databricks Lakehouse Platform for successSee all customersExplore the Burberry storyFeatured Stories
Customer Story
AT&T democratizes data to prevent fraud, reduce churn and increase CLV
Databricks Lakehouse has helped AT&T accelerate AI across operations, including decreasing fraud by 70%–80%
Read more
Customer Story
Shell innovates with energy solutions for a cleaner world
Databricks Lakehouse helps to democratize data and modernize operations globally
Read more
Customer Story
ABN AMRO transforms banking on a global scale
ABN AMRO puts data and Al into action with Databricks Lakehouse
Read more
Customer Story
Rolls-Royce delivers a greener future for air travel
Rolls-Royce decreases carbon through real-time data collection with Databricks Lakehouse
Watch video
Customer Story
Delivering integrity and efficiency for the U.S. Postal Service
USPS OIG supports efficient postal service to millions with Databricks Lakehouse
Read more
Customer Story
Walgreens personalizes pharmacy care to improve patient outcomes
Databricks Lakehouse helps Walgreens personalize patient experiences for over 825 million prescriptions filled annually
Read moreExplore all customersThe Data Team EffectData teams are the united force that are solving the world’s toughest problems.Be the next success storyContact usResourcesCustomer StoryLearn how Databricks enables Condé Nast to deliver personalized content to its customers.Learn moreWebinarLearn how Apple and Disney+ unified analytics and AI for successWatch nowPodcastHear about the role of data and AI in healthcare equity from the CDAO at HumanaWatch nowReady to get started?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/br/solutions/industries/retail-industry-solutions
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A solução de Data Lakehouse para o setor de varejo e CPG - 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 NOWExplorar as soluções lakehouse para o setor de varejoOs dados unificados, as análises e a plataforma de IA que os varejistas usam para fornecer mais em cada fase da jornada do clienteInscrever-seEntre em contatoMelhor desempenho, maior escala, TCO mais baixoLakehouse para o setor de varejoIntegre dados e cargas de trabalho de IA com recursos de compartilhamento integrados e governança para garantir que as equipes internas e externas tenham acesso aos dados de que precisam, no momento certoImpacto em toda a cadeia de valorEngajamento do clienteMais relevante e altamente personalizável em todos os pontos de contatoAo obter uma visão precisa e abrangente de seus clientes em tempo real, os varejistas têm tudo de que precisam para criar relacionamentos personalizados, incluindo entender o sentimento nos canais e personalizar recomendações. O resultado é maior lucratividade e fidelidade.Eficiência operacionalProdutividade dos funcionáriosDesempenho do produtoParceiros e soluções para o setor de varejoSoluções de análises de dados e IA sem compromisso criadas especificamente para o seu setorOs aceleradores de soluções da Databricks são guias criados especificamente para acelerar os resultados usando notebooks totalmente funcionais e práticas recomendadas. Economize tempo de descoberta, design, desenvolvimento e testes em casos de uso, como classificação de propensão, valor do tempo de vida do cliente, otimização da separação de pedidos e muito mais.Previsão refinadaGere previsões em grande escala em menos tempo
Aproveite o poder computacional distribuído da Plataforma Databricks Lakehouse para fazer previsões granulares de maneira mais eficiente no nível de estoque da loja.Comece agoraSegmentação de clientesMelhore a segmentação de clientes
Gere previsões de compra mais precisas com base no comportamento por meio da segmentação avançada de clientes usando dados de vendas, campanhas, sistemas de promoção e muito mais.Comece agoraAnálises de ponto de venda em tempo realCalcule estoques em tempo real em vários locais de loja para melhorar as margens de varejo
Ingira rapidamente todas as fontes e tipos de dados do ponto de venda em escala para obter insights em tempo real que atendam às necessidades urgentes de informações na loja.Comece agoraExplorar aceleradores para o setor de varejoTemos parceria com as principais empresas de consultoria para oferecer soluções inovadoras e dedicadas a cada setor de negócios. As soluções Databricks Brickbuilder ajudam a reduzir custos e maximizar o valor dos seus dados. Elas são apoiadas por décadas de experiência no setor e projetadas para a Plataforma Databricks Lakehouse para atender às suas necessidades.Visão unificada da demandaMaximize a precisão, granularidade e pontualidade com um plano de demanda baseado em uma única fonte confiável.Saiba maisGerenciamento de crescimento de receitaAcelere a análise de dados de faturamento, dados externos de mercado, notícias e dados extraídos da internet para explorar as tendências do varejo.Saiba maisTrellisResolva desafios relacionados a previsões de demanda, reabastecimento, compras, preços e serviços de promoção.Saiba maisExplorar todas as soluções Brickbuilder“Agora, no nível do cliente, podemos combinar informações de compra online e offline, o que antes era uma tarefa difícil. Essa visão omnicanal nos permite construir um mecanismo de recomendação online mais abrangente, que gera um engajamento tremendo.”
— Wendell Kuling, gerente de data science e análises da Jumbo
“A Databricks nos permite oferecer a melhor experiência aos clientes em todos os mercados. Com base na Plataforma Lakehouse, nossos stakeholders e desenvolvedores podem colaborar melhor e obter tendências e insights importantes necessários para atender nossos 180 milhões de clientes.“
— Sergiy Tkachuk, diretor de data science da Reckitt
“Cada vez mais unidades de negócios estão usando a plataforma de maneira self-service, o que antes era impossível. Estou extremamente impressionada com o impacto positivo que o Databricks teve na Columbia.”
— Lara Minor, gerente sênior de dados empresariais, Columbia Sportswear
RecursosTour autoguiadoTodos os recursos de que você precisa para explorar o lakehouse para o setor de varejoWebinarsAceleração da tomada de decisões em tempo real no setor de varejoe-booksBig Book of Retail Use CasesProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers
at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas opções de privacidade|Seus direitos de privacidade na Califórnia
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https://www.databricks.com/company/partners/consulting-and-si/partner-solutions/tensile-ai-accelerated-sas-migration
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SAS Migration Accelerator by Tensile AI and Databricks | 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 SolutionSAS Migration Accelerator by Tensile AIMigration solution developed by Tensile AI and powered by the Databricks Lakehouse Platform
Get startedEnsure a rapid and sound migration processAs organizations continue to modernize data and analytic capabilities with the Databricks Lakehouse Platform, mission-critical SAS applications are often a barrier to realizing the maximum benefits of the cloud. Tensile AI has deep SAS and Databricks expertise with extensive experience leading large-scale data and analytic migrations. Tensile AI’s SAS Migration Accelerator enables the rapid migration of SAS processes with minimal disruption and risk to internal teams, allowing organizations the flexibility to move single, critical workloads or the entire enterprise, according to defined modernization goals. This results in superior performance and cost reduction. With Tensile AI’s solution, you can:Quickly and safely move complex SAS workloads to the cloudAchieve significant savings through product rationalization and licensing costs — the average savings is 35%Increase value through system performance — with an average performance gain of 85%Get 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.
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https://www.databricks.com/blog/2022/06/24/data-warehousing-modeling-techniques-and-their-implementation-on-the-databricks-lakehouse-platform.html
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Different Data Warehousing Modeling Techniques and How to Implement them on the Databricks Lakehouse Platform - 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 SectorData Warehousing Modeling Techniques and Their Implementation on the Databricks Lakehouse PlatformUsing Data Vaults and Star Schemas on the Lakehouseby Soham Bhatt and Deepak SekarJune 24, 2022 in Platform BlogShare this postThe lakehouse is a new data platform paradigm that combines the best features of data lakes and data warehouses. It is designed as a large-scale enterprise-level data platform that can house many use cases and data products. It can serve as a single unified enterprise data repository for all of your:data domains,real-time streaming use cases,data marts,disparate data warehouses,data science feature stores and data science sandboxes, anddepartmental self-service analytics sandboxes.Given the variety of the use cases — different data organizing principles and modeling techniques may apply to different projects on a lakehouse. Technically, the Databricks Lakehouse Platform can support many different data modeling styles. In this article, we aim to explain the implementation of the Bronze/Silver/Gold data organizing principles of the lakehouse and how different data modeling techniques fit in each layer.What is a Data Vault?A Data Vault is a more recent data modeling design pattern used to build data warehouses for enterprise-scale analytics compared to Kimball and Inmon methods.Data Vaults organize data into three different types: hubs, links, and satellites. Hubs represent core business entities, links represent relationships between hubs, and satellites store attributes about hubs or links.Data Vault focuses on agile data warehouse development where scalability, data integration/ETL and development speed are important. Most customers have a landing zone, Vault zone and a data mart zone which correspond to the Databricks organizational paradigms of Bronze, Silver and Gold layers. The Data Vault modeling style of hub, link and satellite tables typically fits well in the Silver layer of the Databricks Lakehouse.Learn more about Data Vault modeling at Data Vault Alliance.A diagram showing how Data Vault modeling works, with hubs, links, and satellites connecting to one another.What is Dimensional Modeling?Dimensional modeling is a bottom-up approach to designing data warehouses in order to optimize them for analytics. Dimensional models are used to denormalize business data into dimensions (like time and product) and facts (like transactions in amounts and quantities), and different subject areas are connected via conformed dimensions to navigate to different fact tables.The most common form of dimensional modeling is the star schema. A star schema is a multi-dimensional data model used to organize data so that it is easy to understand and analyze, and very easy and intuitive to run reports on. Kimball-style star schemas or dimensional models are pretty much the gold standard for the presentation layer in data warehouses and data marts, and even semantic and reporting layers. The star schema design is optimized for querying large data sets.A star schema exampleBoth normalized Data Vault (write-optimized) and denormalized dimensional models (read-optimized) data modeling styles have a place in the Databricks Lakehouse. The Data Vault’s hubs and satellites in the Silver layer are used to load the dimensions in the star schema, and the Data Vault’s link tables become the key driving tables to load the fact tables in the dimension model. Learn more about dimensional modeling from the Kimball Group.Data organization principles in each layer of the LakehouseA modern lakehouse is an all-encompassing enterprise-level data platform. It is highly scalable and performant for all kinds of different use cases such as ETL, BI, data science and streaming that may require different data modeling approaches. Let's see how a typical lakehouse is organized:A diagram showing characteristics of the Bronze, Silver, and Gold layers of the Data Lakehouse Architecture.Bronze layer — the Landing ZoneThe Bronze layer is where we land all the data from source systems. The table structures in this layer correspond to the source system table structures “as-is,” aside from optional metadata columns that can be added to capture the load date/time, process ID, etc. The focus in this layer is on change data capture (CDC), and the ability to provide an historical archive of source data (cold storage), data lineage, auditability, and reprocessing if needed — without rereading the data from the source system.In most cases, it's a good idea to keep the data in the Bronze layer in Delta format, so that subsequent reads from the Bronze layer for ETL are performant — and so that you can do updates in Bronze to write CDC changes. Sometimes, when data arrives in JSON or XML formats, we do see customers landing it in the original source data format and then stage it by changing it to Delta format. So sometimes, we see customers manifest the logical Bronze layer into a physical landing and staging zone.Storing raw data in the original source data format in a landing zone also helps with consistency wherein you ingest data via ingestion tools that don’t support Delta as a native sink or where source systems dump data onto object stores directly. This pattern also aligns well with the autoloader ingestion framework wherein sources land the data in landing zone for raw files and then Databricks AutoLoader converts the data to Staging layer in Delta format.Silver layer — the Enterprise Central RepositoryIn the Silver layer of the Lakehouse, the data from the Bronze layer is matched, merged, conformed and cleaned (“just-enough”) so that the Silver layer can provide an “enterprise view” of all its key business entities, concepts and transactions. This is akin to an Enterprise Operational Data Store (ODS) or a Central Repository or Data domains of a Data Mesh (e.g. master customers, products, non-duplicated transactions and cross-reference tables). This enterprise view brings the data from different sources together, and enables self-service analytics for ad-hoc reporting, advanced analytics and ML. It also serves as a source for departmental analysts, data engineers and data scientists to further create data projects and analysis to answer business problems via enterprise and departmental data projects in the Gold layer.In the Lakehouse Data Engineering paradigm, typically the (Extract-Load-Transform) ELT methodology is followed vs. traditional Extract-Transform-Load(ETL). ELT approach means only minimal or “just-enough” transformations and data cleansing rules are applied while loading the Silver layer. All the “enterprise level” rules are applied in the Silver layer vs. project-specific transformational rules, which are applied in the Gold layer. Speed and agility to ingest and deliver the data in Lakehouse is prioritized here.From a data modeling perspective, the Silver Layer has more 3rd-Normal Form like data models. Data Vault-like write-performant data architectures and data models can be used in this layer. If using a Data Vault methodology, both the raw Data Vault and Business Vault will fit in the logical Silver layer of the lake — and the Point-In-Time (PIT) presentation views or materialized views will be presented in the Gold Layer.Gold layer — the Presentation LayerIn the Gold layer, multiple data marts or warehouses can be built as per dimensional modeling/Kimball methodology. As discussed earlier, the Gold layer is for reporting and uses more denormalized and read-optimized data models with fewer joins compared to the Silver layer. Sometimes tables in the Gold Layer can be completely denormalized, typically if the data scientists want it that way to feed their algorithms for feature engineering.ETL and data quality rules that are “project-specific” are applied when transforming data from the Silver layer to Gold layer. Final presentation layers such as data warehouses, data marts or data products like customer analytics, product/quality analytics, inventory analytics, customer segmentation, product recommendations, marketing/sales analytics etc. are delivered in this layer. Kimball style star-schema based data models or Inmon style Data marts fit in this Gold Layer of the Lakehouse. Data Science Laboratories and Departmental Sandboxes for self-service analytics also belong in the Gold Layer.The Lakehouse Data Organization ParadigmTo summarize, data is curated as it moves through the different layers of a Lakehouse.The Bronze layer uses the data models of source systems. If data is landed in raw formats, it is converted to DeltaLake format within this layer.The Silver layer for the first time brings the data from different sources together and conforms it to create an Enterprise view of the data — typically using a more normalized, write-optimized data models that are typically 3rd-Normal Form-like or Data Vault-like.The Gold layer is the presentation layer with more denormalized or flattened data models than the Silver layer, typically using Kimball-style dimensional models or star schemas. The Gold layer also houses departmental and data science sandboxes to enable self-service analytics and data science across the enterprise. Providing these sandboxes and their own separate compute clusters prevents the Business teams from creating their own copies of data outside of the Lakehouse.This Lakehouse data organization approach is meant to break data silos, bring teams together, and empower them to do ETL, streaming, and BI and AI on one platform with proper governance. Central data teams should be the enablers of innovation in the organization, speeding up the onboarding of new self-service users, as well as the development of many data projects in parallel — rather than the data modeling process becoming the bottleneck. The Databricks Unity Catalog provides search & discovery, governance and lineage on the Lakehouse to ensure good data governance cadence.Build your Data Vaults and star schema data warehouses with Databricks SQL today.How data is curated as it moves through the various Lakehouse layers.Further reading:Five Simple Steps for Implementing a Star Schema in Databricks With Delta LakeBest practices to implement a Data Vault model in Databricks LakehouseDimensional Modeling Best practice & Implementation on Modern LakehouseIdentity Columns to Generate Surrogate Keys Are Now Available in a Lakehouse Near You!Load an EDW Dimensional Model in Real Time With Databricks LakehouseTry Databricks for freeGet StartedRelated postsFive Simple Steps for Implementing a Star Schema in Databricks With Delta LakeMay 20, 2022 by Cary Moore, Lucas Bilbro and Brenner Heintz in Product
Most data warehouse developers are very familiar with the ever-present star schema. Introduced by Ralph Kimball in the 1990s, a star schema is...
Prescriptive Guidance for Implementing a Data Vault Model on the Databricks Lakehouse PlatformJune 24, 2022 by Soham Bhatt, Tanveer Shaikh and Glenn Wiebe in Solutions
There are many different data models that you can use when designing an analytical system, such as industry-specific domain models, Kimball, Inmon, and...
Data Modeling Best Practices & Implementation on a Modern LakehouseOctober 20, 2022 by Leo Mao, Abhishek Dey, Justin Breese and Soham Bhatt in Platform Blog
A Large number of our customers are migrating their legacy data warehouses to Databricks Lakehouse as it enables them to modernize not only...
See all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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https://www.databricks.com/p/webinar/automating-the-ml-lifecycle-with-databricks-machine-learning?itm_data=product-resources-automatingMLlifecycle
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Automating the ML Lifecycle With Databricks Machine Learning | DatabricksOn-demand webinar | Q&AAutomating the ML Lifecycle With Databricks Machine LearningCome learn about the key elements of the machine learning lifecycle and how to automate away the most time-consuming manual, repeated and error-prone processes. In this webinar, we’ll discuss and demonstrate how Databricks Machine Learning can help you automate model training, tuning and the production process — saving you hours of development time.We’ll also cover how data engineers, data scientists, ML engineers and DevOps can collaborate and make the MLOps lifecycle more efficient and productive. Along the way, we’ll highlight the newest capabilities of Databricks Machine Learning, including AutoML, the Feature Store and Model Registry webhooks.Join us to learn how to:Ingest, prepare and featurize dataTune and train modelsManage the model lifecycleServe, monitor and retrain models in productionSpeakerRafi KurlansikSr. Solutions Architect, Machine LearningDatabricksWatch On-demandProductPlatform 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/fr/solutions/industries/manufacturing-industry-solutions
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Solutions pour l'industrie manufacturière – DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT
Au revoir, entrepôt de données. Bonjour, Lakehouse.
Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne.
Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT
Découvrez le Lakehouse pour la fabrication
Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023
Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWDécouvrez le lakehouse pour la fabricationRéduisez vos coûts, optimisez la productivité et unifiez votre écosystème de données sur la seule plateforme conçue pour répondre aux besoins des fabricantsS'inscrireNous contacterUn TCO réduit. De meilleures performances. Davantage d'évolutivité.Le lakehouse pour la fabricationLorsque vous unifiez toutes vos charges de travail de données, d'analytique et d'IA au sein d'une plateforme intégrant le partage et la gouvernance, les équipes internes et externes accèdent aux données dont elles ont besoin au moment voulu.Un impact sur toute la chaîne de valeurEngagement des clientsDes résultats précis et une expérience sans friction pour les clientsLorsque vous avez une vue à 360 degrés sur vos clients, vos opérations et vos actifs, vous pouvez assurer les plus hauts niveaux de disponibilité, de qualité de service et de valeur économique sur l'ensemble du cycle de vie des produits. Cette vue alimente l'individualisation des résultats clients, une approche proactive du service de terrain et l'émergence de solutions stratégiques différenciées.Efficacité opérationnelleProductivité des collaborateursInnovation produitSolutions et partenaires pour la fabricationDes solutions d’analytique et d’IA sans compromis, spécialement pensées pour les fabricantsLes accélérateurs de solutions Databricks sont des guides spécialisés conçus pour accélérer les résultats dans la fabrication, à l'aide de notebooks entièrement fonctionnels et de bonnes pratiques. Gagnez du temps au moment de la découverte, de la conception, du développement et des tests dans des cas d'usage clés : jumeau numérique, efficacité globale des équipements, prévisions, etc.Surveillance de l'efficacité globale des équipements et des KPIAssurez un monitoring performant et évolutif des équipements, de bout en bout
Importez et traitez de façon incrémentielle différents formats de données provenant des capteurs et appareils IoT. Puis calculez et révélez des KPI et des métriques pour produire des insights utiles.DémarrerPrévisions à la pièce prèsAnticipez la demande à la pièce près pour une fabrication rationalisée
Réalisez des prévisions de demande à la pièce près plutôt qu'au niveau global afin de minimiser les perturbations de la chaîne d'approvisionnement et accroître les ventes.DémarrerJumeaux numériquesGagnez en efficacité opérationnelle et améliorez la prise de décision
Traitez les données réelles en continu, calculez des insights à grande échelle pour les injecter dans différentes applications en aval, et optimisez les opérations de l'usine en prenant des décisions data-driven.DémarrerDécouvrez les accélérateurs pour la fabricationNous nous sommes associés à des cabinets de conseil de premier plan pour proposer des solutions innovantes dédiées à chaque secteur d'activité. Les solutions Databricks Brickbuilder vous aident à réduire les coûts et à optimiser la valeur de vos données. Les solutions Brickbuilder s'appuient sur des décennies d’expertise sectorielle et sont pensées pour la plateforme Databricks Lakehouse, pour répondre à vos besoins exacts.Fabrication intelligente Exploitez la puissance de vos données, favorisez l'interopérabilité et générez des insights riches à grande échelle avec l'analytique et l'IA.En savoir plusInspection de la qualitéAutomatisez le contrôle qualité grâce à la vision par ordinateur pour détecter les défauts, les corps étrangers, les anomalies et les erreurs de configuration.En savoir plusUne gestion prédictive du risque d'approvisionnementObtenez une visibilité granulaire sur les flux de commande et les performances des fournisseurs pour gagner en efficacité, gérer les exceptions et améliorer la résilience.En savoir plusDécouvrez toutes les solutions partenaires« Le lakehouse Databricks nous permet de rendre les données plus accessibles dans toute l'organisation, afin de construire les véhicules électriques les plus innovants et les plus fiables au monde. »
– Wassym Bensaid, Vice President of Software Development, Rivian
« Au fil des ans, l’utilisation de Databricks s’est considérablement élargie. Au départ, Databricks était notre plateforme d'IA et de big data, mais les frontières de son champ d'action ont été repoussées. Une classe entièrement nouvelle d'ingénieurs citoyens et de data scientists l'utilise aujourd'hui comme un outil de Business Intelligence moderne pour prendre des décisions commerciales plus éclairées. »
– Daniel Jeavons, Directeur général, Centre d'excellence pour les analytiques avancées, Shell
« La plateforme Databricks nous aide à minimiser les risques pesant sur la disponibilité des moteurs, à réduire les délais d'obtention des pièces détachées et à gérer la rotation des stocks plus efficacement. Et c'est grâce à tout cela que nous délivrons TotalCare, le programme de maintenance Power-by-the-Hour (PBH) numéro un du secteur de l'aviation. »
— Stuart Hughes, Directeur de l'informatique et du numérique, Rolls-Royce Civil Aerospace
Ressourcese-bookExploitez la puissance de vos données ERPWebinairesAméliorer la maintenance prédictive dans la fabrication grâce aux données et à l'IAe-bookQuatre forces motrices pour la fabrication intelligentePrêt à vous lancer ?Nous serions ravis de connaître vos objectifs commerciaux. Notre équipe de services fera tout son possible pour vous aider à réussir.ESSAYER GRATUITEMENT DATABRICKSNous contacterProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterD écouvrez les offres d'emploi
chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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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.Avis de confidentialité|Conditions d'utilisation|Vos choix de confidentialité|Vos droits de confidentialité en Californie
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https://www.databricks.com/dataaisummit/speaker/varun-sharma/#
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Varun Sharma - 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 ExperiencePricingVarun SharmaPrincipal Data Engineer at Visa Inc.Back to speakersVarun Sharma is a Principal Data Engineer at Visa's Data and AI platform, with over a decade of Big Data experience in the finance domain. At Visa, Varun has been instrumental in building a high-performance data engineering platform to power the company's analytics and machine learning applications. Varun has a deep understanding of distributed computing like frameworks like Apache Spark and Hadoop. He's very passionate about making data accessible to everyone.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/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/dataaisummit/speaker/chao-sun
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Chao 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 ExperiencePricingChao SunSoftware Engineer at AppleBack to speakersChao is currently a software engineer working at Apple, focusing on open source Spark.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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Solutions pour le secteur des médias et du divertissement – Databricks Lakehouse – DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT
Au revoir, entrepôt de données. Bonjour, Lakehouse.
Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne.
Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT
Découvrez le Lakehouse pour la fabrication
Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023
Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWDatabricks pour le secteur des médias et du divertissementLes données, l'analytique et l'IA au service de l'avenir des médiasDémarrerPlanifier une démoLes quatre défis liés aux données dans le secteur des médias et du divertissementCréer un profil d'audience unifié
Parce que les données sont collectées, stockées et gérées dans des systèmes disparates, les entreprises de médias ne parviennent pas à obtenir une image globale de leur audience et des informations sur les annonceurs.Offrir une expérience utilisateur exceptionnelle
Les consommateurs attendent en permanence des interactions individualisées et sans friction, sur tous les supports. Le défi : délivrer ces expérience en temps réel, à grande échelle.Exploiter l'intégralité de vos données médias
Les data warehouses traditionnels sont incapables de traiter les données non structurées telles que les fichiers vidéo, image et audio, ce qui empêche les entreprises de libérer tout le potentiel de leurs assets les plus prometteurs.Au-delà de l'agrégation, l'analytique avancée
Les cas d'usage complexes de l'IA concernant le cycle de vie de la publicité et des consommateurs nécessitent actuellement l'acquisition et l'harmonisation de jeux de données massifs, ce qui a un coût considérable.Découvrez Data Lakehouse : le meilleur des deux mondes sur une seule plateformeUn data lakehouse combine le meilleur des data warehouses et des data lakes en une plateforme simple et unique afin de traiter tous vos cas d'usage de données, d'analytique et d'IA. Il s'appuie sur une base de données ouverte et fiable qui traite efficacement tous types de données et applique une approche commune de gouvernance et de sécurité à l'ensemble de vos données et plateformes cloud.En savoir plusLe lakehouse en actionDécouvrez les possibilités du lakehouse Databricks pour votre secteur d'activitéTechnologies marketing et publicitéGérez les marges, apportez à vos opérations une rigueur axée sur les données, améliorez la performances de vos contenus et optimisez le travail créatif pour harmoniser les tâches de vos équipes.En savoir plusDiffusion et streamingCréez des expériences individualisées à grande échelle, améliorez les performances de vos campagnes et extrayez davantage de valeur de l'ensemble de votre portefeuille de contenu.En savoir plusJeux vidéosExploitez les données et l'IA pour améliorer la conception des jeux, accroître l'acquisition et l'engagement des joueurs, et maximiser la monétisation et la fidélisation.En savoir plusPourquoi Databricks pour le secteur des médias et du divertissement ?Toutes vos données, votre analytique et votre IA réunies sur une seule plateforme
Exploitez toute la valeur de vos données pour optimiser l'engagement de vos audiences, vos campagnes et leur monétisation.Optimisé pour le temps réel
Découvrez des insights exploitables, réalisez vos objectifs de personnalisation et améliorez l'expérience de votre audience grâce au machine learning.Accélérer vos résultats commerciaux
Puisez dans nos Accélérateurs de solutions pour ingérer plus facilement les données clients, notamment pour analyser l'engagement sur les flux de clics. Délivrez des cas d'usage puissants comme les moteurs de recommandation et l'attribution multi-contact.Une fiabilité et une performance de premier ordre
Le lakehouse Databricks offre une combinaison inégalée de vitesse, d'évolutivité et de rentabilité. Il n'est pas étonnant que le meilleur data warehouse soit un lakehouse.Transformer le secteur des médias et du divertissement avec le lakehouse
« Avec la plateforme Databricks Lakehouse sur AWS, Warner Bros. Discovery invente le futur de la découverte de contenu et de l'expérience de ses audiences. En exploitant les données pour prédire plus précisément le comportement des consommateurs et proposer des recommandations de contenu individualisées en temps réel, nous personnalisons l'expérience du spectateur et améliorons l'engagement global de nos clients »— Martin Ma, GVP, Ingénierie chez Warner Bros. DiscoveryÉclairages de haut niveau sur les données, l'analytique et l'IADécouvrez les projets menés par d'autres décideurs du secteur des médias et du divertissement pour optimiser leur stratégie de donnéesEn savoir plusQue pouvez-vous faire avec un lakehouse ?
Accélérez vos résultats en termes d'audience et de publicité grâce à une plateforme de données, d'analytique et d'IA collaborative et ouverteUne vue à 360° sur votre audience
Rassemblez toutes vos données, structurées ou non (parcours de navigation, informations démographiques, réseaux sociaux, etc.) au sein d'une même plateforme d'analytique et d'IA. Munies d'une vision holistique du parcours du consommateur, les organisations peuvent interpréter les préférences de contenu et ainsi affiner la personnalisation des expériences et le ciblage de la publicité et de l'engagement.Réduire l'attrition, augmenter l'ARPU
En exploitant une plateforme cloud agile, une entreprise peut rapidement traiter des quantités massives de données avec un haut niveau de fiabilité, puis les injecter dans des systèmes en aval pour délivrer des expériences personnalisées sur tous les canaux, à tout moment. Les consommateurs attendent toujours plus de recommandations en temps réel, et leur attention fait l'objet d'une concurrence féroce parmi les acteurs des médias. Dans ce contexte, une capacité de personnalisation proche du temps réel devient un impératif pour de nombreuses entreprises.Les bibliothèques de contenus comme source de revenus
Les entreprises du secteur des médias se basent sur des données non structurées (fichiers vidéo, image et audio) : elles doivent donc impérativement être en capacité de les analyser pour assurer une gestion efficace de leurs assets multimédia. Le lakehouse pour le monitoring et l'évaluation permet aux responsables marketing d'exploiter les contenus archivés pour élaborer des campagnes. Il permet aussi aux équipes de production de rechercher des contenus existants à intégrer à de nouvelles créations, et aux équipes de vente d'identifier des contenus à vendre à d'autres entreprises du secteur.Exploitez des modèles d'IA / ML prédéfinis. Mettre le ML au cœur de votre activité
Libérez la puissance du machine learning pour mieux comprendre les besoins de vos consommateurs, de vos collaborateurs et de vos annonceurs. Une fois que toutes vos données sont centralisées et connectées de façon transparente par une suite complète d'outils collaboratifs d'analytique et de machine learning, les équipes de données ont la possibilité de créer de puissants modèles prédictifs qui favoriseront l'innovation dans les domaines de la personnalisation, de la monétisation des contenus et de la publicité.Télécharger l'ebookPartenaires et solutions
Prenez un bon départ en choisissant des modèles et des solutions de données et d'analytique spécialement pensés pour le secteur des médias et du divertissement
Découvrez notre portail partenairesAttribution multipointMesurez l'efficacité des campagnes et optimisez les dépenses marketing en améliorant l'attribution des canauxDémarrerToxicité des joueurs et utilisateursPréservez une ambiance saine au sein de vos communautés d'utilisateurs en détectant en temps réel les propos et les comportements toxiquesDémarrerAnalyse de survie / valeur vieIdentifiez les risques de désabonnement chez vos consommateurs et les facteurs qui prolongent leur cycle de vieDémarrerTendance à l'attritionOptimisez la fidélisation, obtenez une vision précise du cycle de vie et réduisez votre taux de désabonnementDémarrerSegmentation comportementaleCréez des segments avancés pour générer de meilleures prévisions d'achat en fonction des comportementsDémarrerPrévision des ventes et attributionOptimisez les résultats de la publicité en ciblant les canaux les plus performantsDémarrerRecommandationsAugmentez les conversions et l'engagement grâce à des recommandations multicanal personnaliséesDémarrerReconnaissance d'image / LabelboxAnnotez des images et des vidéos dans le lakehouse pour orienter le ciblage publicitaire contextuel
Bientôt disponibleQualité de l'expérience vidéoAnalysez les données en batch et en streaming pour garantir les performances de l'expérience en streamingDémarrerEnchères en temps réelApprenez à prédire la visibilité des publicités en temps réel pour affiner votre stratégie RTBDémarrerVoir toutes les solutionsLakehouse pour les médias et le divertissementRessources
Toutes les ressources dont vous avez besoin. Réunies au même endroit.
Explorez notre bibliothèque de ressources : vous y trouverez des ebooks et des vidéos sur les données, l'analytique et l'IA dédiés au secteur des médias et du divertissement
Explorer les ressourcese-bookTÉLÉCHARGER MAINTENANTWebinairesEn savoir plusBlogsEn savoir plusPrêt à vous lancer ?Nous serions ravis de connaître vos objectifs commerciaux. Notre équipe de services fera tout son possible pour vous aider à réussir.ESSAYER GRATUITEMENT DATABRICKSPlanifier une démoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterD écouvrez les offres d'emploi
chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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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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Programa de parceiros de dados | 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 NOWPrograma de parceria com provedores de dadosAcesse o amplo e aberto ecossistema de consumidores de dados com a DatabricksInscreva-se agoraA partir de uma única plataforma, a Databricks ajuda os parceiros provedores de dados a monetizar seus ativos de dados para um grande ecossistema aberto de consumidores de dados. Nossos parceiros podem aproveitar a Databricks Lakehouse Platform para atingir mais clientes, reduzir custos e oferecer a melhor experiência da categoria para todas as suas necessidades de compartilhamento de dados.Benefícios da parceria com provedores de dadosAlcance mais consumidoresCobertura expandida para mais consumidores de dados a partir de uma plataforma aberta e seguraMelhor experiência do clienteTempo reduzido de configuração e ativação para consumidores de dadosSuporte de marketingMaior exposição com o suporte de marketing da DatabricksTecnologia para produtos de dadosA plataforma lakehouse líder de mercado para dados, análises e IAAcesso à equipe de produto e P&DAcesso à equipe de produto, engenharia e suporte da DatabricksSoluções para cada setorTrabalhe com nossas equipes de cada setor para criar soluções específicas projetadas para casos de uso de clientesDelta Sharing para provedores de dadosA Databricks se integra nativamente ao Delta Sharing, o primeiro protocolo aberto do mundo para compartilhamento seguro de dados entre organizações, em tempo real e independentemente da plataforma em que estão.O Delta Sharing tem a aprovação de um grande ecossistemaClientes de código abertoClientes comerciaisBusiness IntelligenceAnálisesGovernançaProvedores de dadosTudo pronto para começar?Inscreva-se agoraEncontrar uma parceriaProdutoVisão 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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Databricks Cloud Provider Directory | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT
Goodbye, Data Warehouse. Hello, Lakehouse.
Attend to understand how a data lakehouse fits within your modern data stack.
Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.
See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco
June 26–29
Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Cloud Provider DirectoryDatabricks Unified Analytics Platform ServicesThe Databricks Unified Analytics Platform Service is available directly from Databricks on the platforms of the following Cloud Service Providers:Cloud Service ProviderApplicable DocumentationPricingAvailable Instance Types**Security Certifications and AttestationsAmazon Web ServicesDocsPricingInstance TypesSOC 2 Type II*, ISO 27001:2013, ISO 27018:2019, HIPAA†, PCI-DSS†Google Cloud PlatformDocsPricingInstance TypesISO 27001:2013, ISO 27018:2019 Please note that usage of Databricks Platform Services Workspaces may not count towards your Universal Commitment / Minimum Commitment unless we confirm otherwise in writing from [email protected]. Please note that certain products and features may not be available on GCP. Please see here for details.Databricks Powered ServicesThe Databricks Runtime data processing engine also powers the following Databricks Powered Services:Azure Databricks (provided by Microsoft Corporation)Databricks Data Insights (provided by Alibaba Cloud)Databricks does not provide the Databricks Powered Services to Customers directly; in order to use a Databricks Powered Service, you must enter into a contract with the relevant provider listed above. Please note that usage of Databricks Powered Services may not count towards your Universal Commitment / Minimum Commitment unless we confirm otherwise in writing from [email protected].Databricks may update this Directory at any time to add additional Cloud Service Providers and Databricks Powered Services.*Report available under NDA.Please note that the SOC 2 Type II Report does not yet cover Databricks on GCP. Databricks expects to add Databricks on GCP to our SOC 2 Type II Report in Q4 of 2021. **Available instance types are updated according to available instance types on an applicable Cloud Provider and may change. † Only available for certain deployment types. Please speak to a Databricks sales representative for further information.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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https://www.databricks.com/dataaisummit/speaker/corey-zwart
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Corey Zwart - 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 ZwartChief Technology Officer at PumpJack DataworksBack to speakersCorey is an accomplished DevOps Engineer and Cloud Architect, consistently recognized for his reliability, dependability, & integrity in achieving technical outcomes. Corey serves as the Chief Technology Officer for Pumpjack Dataworks.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/xiao-li
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Xiao 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 ExperiencePricingXiao LiSenior Engineering Manager at DatabricksBack to speakersXiao Li is a senior engineering manager, Apache Spark Committer and PMC member at Databricks. His main interests are on Spark and database engine. Previously, he was an IBM master inventor and an expert on asynchronous database replication and consistency verification. He received his Ph.D. from University of Florida in 2011.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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What are Dense Tensors?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 NOWDense TensorAll>Dense TensorTry Databricks for freeGet StartedDense tensors store values in a contiguous sequential block of memory where all values are represented. Tensors or multi-dimensional arrays are used in a diverse set of multi-dimensional data analysis applications. There are a number of software products that can perform tensor computations, such as the MATLAB suite that has even been enhanced by various open source third party toolboxes. MATLAB alone is capable of supporting a variety of element-wise and binary dense tensor operations A dense layer is a fully connected layer, as each and every neuron gets an input from all the neurons in the previous layer, thus being densely connected. This means that every Neuron in a Dense layer will be fully connected to every Neuron in the prior layer. Dense is usually used towards the end of a network, and sometimes multiple times. Trying to build a layered infrastructure for high-performance dense tensor applications, one of the most used libraries is dten, which is known for storing and manipulating dense tensors. The library focuses on storing dense tensors in canonical storage formats and converting between storage formats in parallel. In addition, it supports tensor matricization in different ways. The library is general-purpose and provides a high degree of flexibility. We may regard a tensor as the multidimensional generalization of a matrix. Mathematically, matricization is merely a conceptual (or logical) restructuring of the tensor.Additional ResourcesTensorFlow™ on DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights
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https://www.databricks.com/fr/product/pricing
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Tarifs de Databricks | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT
Au revoir, entrepôt de données. Bonjour, Lakehouse.
Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne.
Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT
Découvrez le Lakehouse pour la fabrication
Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023
Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWProlongation de la promotion SQL – Économisez 40 % ou plus Profitez de notre promotion de 15 mois sur Serverless SQL et le tout nouveau SQL ProEn savoir plusTarifs de DatabricksUne plateforme simple pour centraliser toutes vos charges de travail de données, d'analytique et d'IA, sur l'ensemble de vos cloudsDémarrez votre essai gratuitComment fonctionnent les tarifs de Databricks ?Payez à l'utilisationDatabricks offre une approche de paiement à l'utilisation sans frais initiaux. Ne payez que les produits que vous utilisez, à la seconde près.Économisez davantage avec les remises pour engagement d'utilisationDatabricks vous permet de réduire vos coûts grâce à des remises lorsque vous vous engagez à respecter certains niveaux d'utilisation. Plus votre engagement d'utilisation est élevé, plus la remise sera importante par rapport au paiement à l'usage. L'utilisation des engagements de dépenses est très souple : vous pouvez les répartir sur plusieurs clouds. Contactez-nous pour plus d'informations.Découvrir les produitsWorkflows et StreamingTâchesStarting at $0.07 / DBUExécutez des pipelines de data engineering pour créer des data lakes et gérer les données à grande échelleEn savoir plusWorkflows et Streaming Delta Live tablesStarting at $0.20 / DBUCréez facilement des pipelines ETL de qualité en batch ou en streaming, en utilisant Python ou SQL avec l'édition DLT qui convient le mieux à votre charge de travailEn savoir plusEntreposage des donnéesDatabricks SQLStarting at $0.22 / DBUExécutez des requêtes SQL pour produire des rapports BI, des analytiques et des visualisations, et obtenir ainsi de précieux insights à partir de vos data lakes. Disponible en deux versions : Classic Compute et Serverless Compute (managé).En savoir plusData Science et Machine LearningTout usageStarting at $0.40 / DBUExécutez des charges de travail interactives en data science et en machine learning. Convient également au data engineering, à la BI et à l'analytique.En savoir plusData Science et Machine LearningInférence serverless en temps réelStarting at $0.07 / DBUFaites des prédictions en direct dans vos applications et vos sites web.
En savoir plusPlateforme Databricks et extensionsPlateforme Databricks et extensionsNiveaux de plateforme : Des fonctionnalités multiplateforme qui offrent le niveau idéal de gestion, de gouvernance et de sécurité pour toutes les charges de travail, des plus simples aux plus stratégiques
Extensions de plateforme : Des améliorations touchant tous les produits de la plateforme Databricks, pour améliorer les capacités de gestion, de gouvernance et de sécuritéEn savoir plusESSAYER GRATUITEMENT DATABRICKSEssayer gratuitementPlanifier une démoFAQQue contient l'essai gratuit ?Les avantages de l'essai gratuit pendant 14 jours :Un environnement collaboratif permettant aux équipes data de créer des solutions de manière collaborativeDes notebooks interactifs pour utiliser Apache SparkTM, SQL, Python, Scala, Delta Lake, MLflow, TensorFlow, Keras, scikit-learn et bien d'autres encoreVeuillez noter que votre fournisseur de cloud vous facturera quand même les ressources – les instances de calcul, notamment – utilisées au sein de votre compte pendant l'essai gratuit.Que se passe-t-il à la fin de l'essai gratuit ?À la fin de la période d'essai, vous bénéficierez d'un abonnement automatique au plan auquel vous avez souscrit lors de votre essai gratuit. Vous pourrez annuler votre abonnement à tout moment.Les tarifs sont-il basés sur l'utilisation ou le volume de stockage ?Les tarifs de Databricks sont basés sur votre utilisation du calcul. Le stockage, le réseau et les coûts associés varient en fonction des services que vous choisissez et de votre fournisseur cloud.Qu'est-ce qu'une DBU ?Une unité Databricks (DBU) est une unité normalisée de puissance de traitement sur la plateforme Lakehouse de Databricks utilisée à des fins de mesure et de tarification. Le nombre de DBU consommées par une charge de travail dépend de mesures de traitement qui peuvent inclure les ressources de calcul utilisées et la quantité de données traitées. Les tarifs sont-ils les mêmes dans toutes les régions ?Les prix de Databricks et ceux de l'infrastructure cloud peuvent varier en fonction de votre région et du fournisseur de services cloud. Pour plus d'informations, consultez les pages de tarification de Databricks propres à chaque produit.Databricks est-il aussi économique que les autres services cloud ou solutions open source ?Le prix des produits Databricks a pour but de proposer aux clients un coût total de possession (TCO) compétitif pour leurs charges de travail. Pour estimer vos économies avec Databricks, il est essentiel de tenir compte des aspects clés des solutions alternatives : taux d'exécution des tâches, durée, effort manuel et ressources requises pour soutenir une tâche. Pour vous aider à estimer vos économies avec précision, nous vous recommandons de comparer les résultats obtenus avec un déploiement servant de test de faisabilité. Par exemple, voyez le gain de temps réalisé par ce client et les résultats du comparatif de ce client. Contactez-nous pour démarrer.En quoi consiste Databricks Community Edition ?Databricks Community Edition est une plateforme gratuite, aux fonctionnalités limitées, conçue pour quiconque souhaite s'initier à Spark. Inscrivez-vous ici.Comment serais-je facturé ?Par défaut, un prélèvement mensuel sera effectué sur votre carte bancaire en fonction du nombre de secondes utilisées. Contactez-nous pour d'autres options de facturation, telles que le paiement sur facture ou sous forme de forfait annuel.Proposez-vous une assistance technique ?Nous proposons une assistance technique. Vous pouvez aussi consulter la documentation technique. Contactez-nous pour en savoir plus.ProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterD écouvrez les offres d'emploi
chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité|Conditions d'utilisation|Vos choix de confidentialité|Vos droits de confidentialité en Californie
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https://www.databricks.com/dataaisummit/speaker/seth-babcock
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Seth Babcock - 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 ExperiencePricingSeth BabcockHead of Connected Aviation Tech Ops Solutions and Analytics at Collins AerospaceBack 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/p/ebook/apache-spark-under-the-hood
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Apache Spark™ Under the Hood | DatabricksApache Spark™ Under the HoodGetting started with core architecture and basic conceptsApache Spark™ has seen immense growth over the past several years, becoming the de-facto data processing and AI engine in enterprises today due to its speed, ease of use, and sophisticated analytics. Spark unifies data and AI by simplifying data preparation at massive scale across various sources, providing a consistent set of APIs for both data engineering and data science workloads, as well as seamless integration with popular AI frameworks and libraries such as TensorFlow, PyTorch, R and SciKit-Learn.Databricks, founded by the team that originally created Apache Spark, is proud to share excerpts from the book, Spark: The Definitive Guide. Enjoy this free mini-ebook, courtesy of Databricks.In this eBook, we cover:The past, present, and future of Apache Spark.Basic steps to install and run Spark yourself.A summary of Spark’s core architecture and concepts.Spark’s powerful language APIs and how you can use them.Get the eBook to learn more.Get the eBookProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights
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https://www.databricks.com/solutions/accelerators
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Databricks Solution Accelerators - Deliver Data & AI Value Faster - 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 NOWIndustry SolutionsDeliver the data and AI-driven outcomes that matter most — fasterStart your free trialDatabricks Solution AcceleratorsSave hours of discovery, design, development and testing with Databricks Solution Accelerators. Our purpose-built guides — fully functional notebooks and best practices — speed up results across your most common and high-impact use cases. Go from idea to proof of concept (PoC) in as little as two weeks.
Start using Solution Accelerators with your free Databricks trial or your existing account.
Start your free trial todayBrowse AcceleratorssearchHide filtersIndustrySortDatabricksToxicity Detection in GamingfeaturedDatabricksOn-Shelf AvailabilityfeaturedDatabricksFine-Grained Demand Forecastingfeatured🔥DatabricksAutomated PHI RemovalfeaturednewDatabricksAbstracting Real-World Data for OncologyDatabricksAnti-Money LaunderingDatabricksCohort Building with Knowledge GraphsDatabricksComputer Vision FoundationsDatabricksCustomer Entity ResolutionDatabricksCustomer Lifetime Value🔥DatabricksCustomer SegmentationSplunkCyber Analytics (Splunk Connector)DatabricksDetecting Adverse Drug EventsnewDatabricksDigital Pathology Image AnalysisDatabricksDigital TwinsDatabricksESG Performance Analytics🔥DatabricksFHIR Interoperability with dbigniteDatabricksFuzzy Item MatchingDatabricksGenome-Wide Association StudiesDatabricksGeospatial Analytics to Identify FraudDatabricksHL7v2 Interoperability With SmolderDatabricksMedia Mix Modeling (MMM)DatabricksMedicare Risk AdjustmentDatabricksMerchant ClassificationDatabricksModern Investment PlatformDatabricksMulti-Touch AttributionDatabricksOptimized Order PickingDatabricksOverall Equipment EffectivenessDatabricksPredictive Maintenance (IoT)DatabricksPrice TransparencynewDatabricksProduct Quality InspectionDatabricksPropensity ScoringnewDatabricksR&D Optimization with Knowledge GraphsnewDatabricksReal-Time Bidding OptimizationDatabricksReal-Time Financial Fraud PreventionDatabricksReal-Time Point-of-Sale AnalyticsnewDatabricksReal-world EvidenceDatabricksRecommendation EngineDatabricksRegulatory ReportingDatabricksReputation RiskDatabricksRetention ManagementDatabricksRisk ManagementDatabricksSafety StockDatabricksSales Forecasting & Ad Attribution🔥DatabricksScalable Route GenerationDatabricksSocial Determinants of HealthDatabricksSubscriber Churn PredictionDatabricksSupply Chain Distribution OptimizationDatabricksSurvival Analysis & Lifetime ValueDatabricksThreat Detection with DNSDatabricksVideo Quality of ExperienceFAQHow much do Solution Accelerators cost?Solution Accelerators are available to any Databricks customer free of charge.Do I need to be a Databricks customer to use a Solution Accelerator?You can implement Solution Accelerators with a free Databricks trial or with your existing Databricks account.What can I expect from a Solution Accelerator?Solution Accelerators are designed to help you save hours of discovery, design, development and testing. Our goal is to jump-start your data and AI use cases by providing the right resources (notebooks, proven patterns and best practices). You can expect to go from idea to proof of concept (PoC) in as little as two weeks.See how actual customers use DatabricksExplore Customer StoriesProductPlatform 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/solutions/accelerators/identifying-fraud
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Identify credit card fraud with geospatial analytics and AI | 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 AcceleratorIdentify Fraud With Geospatial Analytics and AIPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAnalyze geospatial behaviors at scale to identify anomalous card transactionsLearn how geospatial data, machine learning and a lakehouse architecture enable organizations to better understand customer spending behaviors, and detect abnormal credit card transaction patterns in real time. Geospatial analysis can enhance fraud prevention, mitigate losses and build customer trust.Augment analytics with geospatial data at scaleUncover “normal” behavior to identify the abnormalGet real-time customer spending insightsDownload notebookResourcesCase studyLearn moreEngineering blogLearn moreCompany blogLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights
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https://www.databricks.com/dataaisummit/speaker/mohan-kolli
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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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https://www.databricks.com/glossary/predictive-analytics
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What is Predictive Analytics?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 NOWPredictive AnalyticsAll>Predictive AnalyticsWhat is Predictive Analytics?Predictive analytics is a form of advanced analytics that uses both new and historical data to determine patterns and predict future outcomes and trends.How Does Predictive Analytics Work?Predictive analytics uses many techniques such as statistical analysis techniques, analytical queries, data mining, predictive modeling, and automated machine learning algorithms to data sets to create predictive models that place a numerical value on the likelihood of a particular event happening and includes what-if scenarios and risk assessment. With predictive analytics, organizations can find and exploit patterns contained within data in order to detect risks and opportunities. Predictive analytics is usually associated with big data, Engineering data, for example, is retrieved from sensors, instruments, and other connected systems. On the other hand, business system data of an organization could incorporate transaction data, sales results, customer complaints, and marketing information. In order to extract value from big data, companies apply algorithms to large data sets using tools like Hadoop and Spark. These can capture, store and process the large volumes of data structured or unstructured, from different sources like connected devices and sensors that measure your business.Different Stages of Predictive Analytics Life CyclePredictive analytics has its own life cycle; its first lifecycle starts with the problem statement that is its birth and goe up to its replacement by another model. Here are the stages of predictive analytics: Predictive analytics can help you make confident real-time recommendations that reduce costs, improve safety, and inform investments.Additional ResourcesCutting Edge Predictive AnalyticsHealthcare Predictive Analytics within the ORHow Sellpoints Launched a New Predictive Analytics Product with DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights
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https://www.databricks.com/blog/2020/08/03/modern-industrial-iot-analytics-on-azure-part-1.html
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How to Use Databricks to Scale Modern Industrial IoT Analytics - Part 1 - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT
Goodbye, Data Warehouse. Hello, Lakehouse.
Attend to understand how a data lakehouse fits within your modern data stack.
Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.
See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco
June 26–29
Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorModern Industrial IoT Analytics on Azure - Part 1Customers Leverage Azure Databricks for Industrial IoT Analyticsby Samir Gupta, Lana Koprivica and Hubert DuanAugust 3, 2020 in Company BlogShare this post
This post and the three-part series about Industrial IoT analytics were jointly authored by Databricks and members of the Microsoft Cloud Solution Architecture team. We would like to thank Databricks Solutions Architect Samir Gupta and Microsoft Cloud Solution Architects Lana Koprivica and Hubert Dua for their contributions to this and the two forthcoming posts.
The Industrial Internet of Things (IIoT) has grown over the last few years as a grassroots technology stack being piloted predominantly in the oil & gas industry to wide scale adoption and production use across manufacturing, chemical, utilities, transportation and energy sectors. Traditional IoT systems like Scada, Historians and even Hadoop do not provide the big data analytics capabilities needed by most organizations to predictively optimize their industrial assets due to the following factors.ChallengeRequired CapabilityData volumes are significantly larger & more frequentThe ability to capture and store sub-second granular readings reliably and cost effectively from IoT devices streaming terabytes of data per dayData processing needs are more complexACID-compliant data processing - time-based windows, aggregations, pivots, backfilling, shifting with the ability to easily reprocess old dataMore user personas want access to the dataData is an open format and easily shareable with operational engineers, data analysts, data engineers, and data scientists without creating silosScalable ML is needed for decision makingThe ability to quickly and collaboratively train predictive models on granular, historic data to make intelligent asset optimization decisionsCost reduction demands are higher than everLow-cost on-demand managed platform that scales with the data and workloads independently without requiring significant upfront capital
Read Rise of the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data warehouse, Bill Inmon.Organizations are turning to cloud computing platforms like Microsoft Azure to take advantage of the scalable, IIoT-enabling technologies they have to offer that make ingesting, processing, analyzing and serving time-series data sources like Historians and SCADA systems easy.In part 1, we discuss the end-to-end technology stack and the role Azure Databricks plays in the architecture and design for the industrial application of modern IoT analytics.In part 2, we will take a deeper dive into deploying modern IIoT analytics, ingest real-time IIoT machine-to-machine data from field devices into Azure Data Lake Storage and perform complex time-series processing on Data Lake directly.In part 3, we will look at machine learning and analytics with industrial IoT data.The Use Case - Wind Turbine OptimizationMost IIoT Analytics projects are designed to maximize the short-term utilization of an industrial asset while minimizing its long-term maintenance costs. In this article, we focus on a hypothetical energy provider trying to optimize its wind turbines. The ultimate goal is to identify the set of optimal turbine operating parameters that maximizes each turbine’s power output while minimizing its time to failure.The final artifacts of this project are:An automated data ingestion and processing pipeline that streams data to all end usersA predictive model that estimates the power output of each turbine given current weather and operating conditionsA predictive model that estimates the remaining life of each turbine given current weather and operating conditionsAn optimization model that determines the optimal operating conditions to maximize power output and minimize maintenance costs thereby maximizing total profitA real-time analytics dashboard for executives to visualize the current and future state of their wind farms, as shown below:The Architecture - Ingest, Store, Prep, Train, Serve, VisualizeThe architecture below illustrates a modern, best-of-breed platform used by many organizations that leverages all that Azure has to offer for IIoT analytics.A key component of this architecture is the Azure Data Lake Store (ADLS), which enables the write-once, access-often analytics pattern in Azure. However, Data Lakes alone do not solve the real-world challenges that come with time-series streaming data. The Delta storage format provides a layer of resiliency and performance on all data sources stored in ADLS. Specifically for time-series data, Delta provides the following advantages over other storage formats on ADLS:Required CapabilityOther formats on ADLS Gen 2Delta Format on ADLS Gen 2Unified batch & streamingData Lakes are often used in conjunction with a streaming store like CosmosDB, resulting in a complex architectureACID-compliant transactions enable data engineers to perform streaming ingest and historically batch loads into the same locations on ADLSSchema enforcement and evolutionData Lakes do not enforce schema, requiring all data to be pushed into a relational database for reliabilitySchema is enforced by default. As new IoT devices are added to the data stream, schemas can be evolved safely so downstream applications don’t failEfficient UpsertsData Lakes do not support in-line updates and merges, requiring deletion and insertions of entire partitions to perform updatesMERGE commands are effective for situations handling delayed IoT readings, modified dimension tables used for real-time enrichment, or if data needs to be reprocessed.File CompactionStreaming time-series data into Data Lakes generates hundreds or even thousands of tiny files.Auto-compaction in Delta optimizes the file sizes to increase throughput and parallelism.Multi-dimensional clusteringData Lakes provide push-down filtering on partitions onlyZORDERing time-series on fields like timestamp or sensor ID allows Databricks to filter and join on those columns up to 100x faster than simple partitioning techniques.SummaryIn this post we reviewed a number of different challenges facing traditional IIoT systems. We walked through the use case and the goals for modern IIoT analytics, shared a repeatable architecture that organizations are already deploying at scale and explored the benefits of Delta format for each of the required capabilities.In the next post we will ingest real-time IIoT data from field devices into Azure and perform complex time-series processing on Data Lake directly.They key technology that ties everything together is Delta Lake. Delta on ADLS provides reliable streaming data pipelines and highly performant data science and analytics queries on massive volumes of time-series data. Lastly, it enables organizations to truly adopt a Lakehouse pattern by bringing best of breed Azure tools to a write-once, access-often data store.What’s Next?Learn more about Azure Databricks with this 3-part training series and see how to create modern data architectures by attending this webinar.Try Databricks for freeGet StartedRelated postsModern Industrial IoT Analytics on Azure - Part 1August 3, 2020 by Samir Gupta, Lana Koprivica and Hubert Duan in Company Blog
This post and the three-part series about Industrial IoT analytics were jointly authored by Databricks and members of the Microsoft Cloud Solution Architecture...
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Scott Meier - 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 MeierDirector, Data Analytics Service, Financial Services Center at U.S. Department of Veterans AffairsBack 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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Jason Shiverick - 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 ExperiencePricingJason ShiverickData Platform Manager at RivianBack 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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Greg Nelson - 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 ExperiencePricingGreg NelsonVP of Data Operations at Highmark HealthBack to speakersGreg Nelson, MMCi, CPHIMS, FACHE serves as the Vice President, of Data Operations and is a key member of the executive leadership team for the Enterprise Data and Analytics organization at Highmark Health.
Before joining Highmark, Greg held leadership roles at Intermountain Healthcare and ECU Health (formerly Vidant Health.) Greg was also the founder and CEO of ThotWave, a healthcare analytics advisory firm specializing in helping organizations mature their analytics maturity.
Greg serves as an expert for the International Institute for Analytics (IIA) and as adjunct faculty at Duke University, where he teaches advanced analytics to master’s level students in both the School of Nursing and the Fuqua School of Business.
An author with over 200 papers and publications, Mr. Nelson is a regular speaker and keynote presenter at national and international events as well as is also an educator and futurist for industry and association events. As an analytics evangelist and futurist, Greg has brought his 20+ years of analytics advisory work to bear through a recently published book addressing the people and process sides of analytics entitled The Analytics Lifecycle Toolkit (Wiley, 2018). Through this pragmatic treatment of the analytics lifecycle, Greg speaks to both the practical and human-centeredness of analytics in a way that is accessible and useful for all.
Mr. Nelson earned his bachelor’s degree in Psychology from the University of California, Santa Cruz, a Master of Management in Clinical Informatics from Duke University, and conducted Ph.D. level work (ABD) in Social and Cognitive Psychology and Quantitative Methods from the University of Georgia.
You can connect with Greg on Twitter @gregorysnelson or LinkedIn at www.linkedin.com/in/gregorysnelson/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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Combine your data and analytics workloads on one platform | DatabricksOn-DemandDriving healthcare innovations with lakehouseHow CRISP saved lives with dataAvailable on-demandWatch to discover the power of Lakehouse for Healthcare and Life Sciences and how it’s revolutionizing the industry by bringing together all your data and analytics workloads to enable transformative innovations in patient care and drug R&D.During the pandemic, the Maryland Department of Health asked Chesapeake Regional Information System for our Patients (CRISP) to provide demographic data to track COVID-19. This would have been impossible to do manually. That’s why CRISP implemented a data platform powered by Databricks and Delta Lake. The organization then processed billions of records from hundreds of sources to help fight the pandemic.Watch to find out how CRISP:Tracked the path of the pandemicDelivered better patient outcomes with the power of data and AIProvided near real-time reporting of key COVID-19 measuresHelped improve access to testing for vulnerable communitiesSpeakersMichael SankyRVP of Industry SolutionsDatabricksAndy HanksAnalytics Platform OwnerCRISPSteve DowlingData EngineerSlalom ConsultingWatch nowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
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Harrison Chase - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHarrison ChaseCEO at LangChainBack to speakersHarrison Chase is the co-founder and CEO of LangChain, a company formed around the open-source Python/Typescript packages that aim to make it easy to develop Language Model applications. Prior to starting LangChain, he led the ML team at Robust Intelligence (an MLOps company focused on testing and validation of machine learning models), led the entity linking team at Kensho (a fintech startup), and studied stats and CS at Harvard.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
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What is the Databricks Unified Data Analytics Platform?PlatformThe 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 NOWUnified Data Analytics PlatformAll>Unified Data Analytics PlatformDatabricks' Unified Data Analytics Platform helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks as your Unified Data Analytics Platform, you can quickly prepare and clean data at massive scale with no limitations. The platform also enables you to continuously train and deploy ML models for all of your artificial intelligence applications. The top 3 advantages with a Unified Data Analytics Platform are:Innovate faster with big dataMake big data simpleUnifying data science and data engineeringAdditional ResourcesUnified Cloud Data Analytics PlatformUnified Data Analytics - Simplifying Streaming Analytics with Delta Lake and Spark WebinarModern Cloud Data Platform for Dummies eBookBack 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
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Partner Connect | 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
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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 NOWPartner ConnectEasily discover and integrate data, analytics and AI solutions with your lakehouseWatch demosPartner Connect makes it easy for you to discover data, analytics and AI tools directly within the Databricks platform — and quickly integrate the tools you already use today. With Partner Connect, you can simplify tool integration to just a few clicks and rapidly expand the capabilities of your lakehouse.Connect your data and AI tools to the lakehouseEasily connect your preferred data and AI tools to the lakehouse and power any analytics use caseDiscover validated data and AI solutions for new use casesA one-stop portal for validated partner solutions so you can build your next data application fasterSet up in a few clicks with pre-built integrationsPartner Connect simplifies your integrations by automatically configuring resources — including clusters, tokens and connection files — to connect with partner solutionsGet started as a partnerDatabricks partners are uniquely positioned to deliver faster analytics insights for customers. Take advantage of Databricks’ development and partner resources to grow alongside our open, cloud-based platform.Become a partner“Building on our longtime partnership, Partner Connect enables us to design an integrated experience between our companies and customers. With Partner Connect, we’re delivering a streamlined experience that makes it easier than ever for the thousands of Databricks customers, whether they use Fivetran today or discover us through Partner Connect, to unlock insights in their data, discover more analytics use cases, and get value from their lakehouse faster by easily connecting hundreds of data sources to their lakehouse.”— George Fraser, CEO at FivetranDemosFivetranConnect data from 180+ popular apps, including SaaS apps (Salesforce, Google Analytics, etc.) into the lakehousedbtGet started with dbt Cloud and Databricks to build data transformationsPower BIBring the advantages of Databricks Lakehouse performance and technology to all your usersTableauEmpower all users with a data lakehouse for modern analytics by connecting Tableau Desktop to Databricks SQLRiverySimplify the data journey from ingestion to transformation and delivery into Delta LakeLabelboxEasily prepare unstructured data for AI and Analytics in the LakehouseProphecyBuild and deploy Spark and Delta pipelines using a visual drag-and-drop interfaceArcionConnect data sources to the lakehouse with a distributed CDC-based replication platformTry for freeResourcesBlogFeb 2023 – Announcing New Partner Integrations in Partner ConnectSept 2022 – Introducing New Partner Integrations in Partner ConnectJune 2022 – Announcing New Partner Integrations in Partner ConnectBuild Your Business on Databricks With Partner ConnectDocumentationDatabricks Partner Connect guideReady to learn more?Take advantage of Databricks’ development and partner resources to grow alongside our open, cloud-based platform.Become a partnerContact 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
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William Zanine - 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 ExperiencePricingWilliam ZanineHead of Data Management, Channel and Specialty North America at IQVIABack 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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Benefits | 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
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Accelerate Business Value With Delta Sharing | DatabricksOn-DemandAccelerate Business Value With Delta SharingDiscover how to monetize your data and drive greater insightsAvailable on-demandData sharing is crucial to drive business value in today’s digital economy. Organizations are looking to securely share data with their partners/vendors, internal line of business, and generate revenue streams with data monetization. Databricks Delta Sharing empowers organizations to seamlessly and securely share and consume live data without the limitations enforced by vendor-specific sharing networks or constraints of legacy delivery systems like sFTP.Watch this webinar to learn how SafeGraph and Jefferies Group are leveraging Delta Sharing, the industry’s first open protocol for secure data sharing, to enhance their data delivery and unlock business value of data with enriched location data to provide unique insights.In this webinar you will learn:How Delta Sharing is helping data providers like SafeGraph streamline solutions to share dataHow Delta Sharing is helping SafeGraph reduce the “cost of curiosity” for data consumers like JefferiesHow Jefferies Group leverages SafeGraph’s location data to power unique insights in financial servicesSpeakersRayne GaisfordGlobal Head of Data StrategyEquity Research Jefferies LLCJames LaVersaEnterprise Customer Success ManagerSafeGraphJay BhankhariaSenior Director, Data Provider PartnershipsDatabricksWatch NowProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
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Legacy System Migration 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 SolutionLegacy System Migration by AvanadeMigration solution developed by Avanade and powered by the Databricks Lakehouse PlatformGet startedMove your data to unlock its full valueAzure Databricks is a key enabler for helping organizations scale AI and unlock the value of disparate and complex data. To achieve your AI aspirations and uncover insights that inform better decisions, you can migrate your data to a modern, state-of-the-art data platform and turn it into action and value. If you are looking to accelerate data transformation, Avanade can help you quickly move your data from proprietary and expensive legacy systems to drive operational efficiencies and speed up innovation on the lakehouse. No matter where you are in your data and AI maturity, there is still time and opportunity to transform the value driven from your data by migrating to the Azure Platform and leveraging Azure Databricks.2x faster access to data on the cloud through rapid migration strategy, tools and accelerators30% lower TCO through a streamlined data migration journeyGet 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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https://www.databricks.com/dataaisummit/speaker/blaise-sandwidi/#
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Blaise Sandwidi - 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 ExperiencePricingBlaise SandwidiLead Data Scientist, As. ESG Officer, PhD at International Finance Corporation (IFC)–World Bank GroupBack to speakersBlaise Sandwidi is a Lead Data Scientist with IFC’s ESG Global Advisory team. Blaise oversees the development of data science to support ESG risk modeling and data science for development. His past work experience includes positions with private sector institutions focused on building machine learning platforms to enable better investment decisions. Blaise holds a Ph.D. and a master’s degree in finance from the University of Paris-Est, France.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/learn
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Formazione | 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 NOWFormazioneImmergiti in Databricks e scopri un mondo di risorse a portata di mano: formazione e certificazione, eventi, documentazione e molto altro.Primi passi con DatabricksImpara i fondamentiDatabricks Lakehouse Platform agevola la costruzione e l'esecuzione di pipeline di dati, la collaborazione su progetti di data science e analisi, la costruzione e implementazione di modelli di machine learning. Legge le nostre guide per cominciare a utilizzare la soluzione.Sei un nuovo arrivato in Databricks? Comincia il tuo percorso in azienda sotto la guida in un Customer Success Engineer esperto.Onboarding in Databricks
Lakehouse Fundamentals Training
Watch 4 short videos, take the quiz and get your badge
to share on LinkedIn or your résumé
Get startedData science e ingegneria dei datiAmministratori di DatabricksAnalisi SQLMachine LearningFormazioneSegui i corsi della Databricks Academy. Scopri come padroneggiare l'analisi dei dati dal team che ha avviato il progetto di ricerca Apache Spark™️ all'Università di Berkeley.Databricks AcademyCertificazioneGli esami di certificazione valutano il livello di conoscenza della Databricks Lakehouse Platform e delle metodologie per realizzare con successo progetti di qualità. La certificazione favorisce il riconoscimento da parte degli operatori di settore, aiuta a distinguersi dalla concorrenza, ad aumentare la produttività e a migliorare i risultati, oltre a essere una prova tangibile dell'investimento in formazione.Certificazione DatabricksTrova le risposte alle tue domandeScegli uno dei canali disponibili per chiarimenti su dubbi e domande che potrebbero insorgere nella fase iniziale:Parla con un tecnico di Databricks in direttaCommunity onlineEsplora gli argomenti più discussi nella community di Databricks.Unisciti alla communityArgomenti più ricorrenti nei forumdatabricksDelta LakesparksqlpysparkazureawsGCPServe aiuto immediato?Se hai un contratto di assistenza o sei interessato a sottoscriverne uno, verifica le opzioni disponibili. Per richiedere una consulenza strategica (con un Customer Success Engineer o un contratto Professional Services), rivolgiti all'amministratore del tuo spazio di lavoro per entrare in contatto con il tuo Databricks Account Executive.Scoprite le nostre opzioni di supportoGalleria NotebookQuesta galleria mostra alcune possibilità offerte dai Notebook, focalizzate su tecnologie e casi applicativi, che possono essere facilmente importate nell'ambiente di Databricks o nell'edizione gratuita per community.Galleria dei notebook di DatabricksDocumentazioneIl sito con la documentazione tecnica di Databricks fornisce guide pratiche e informazioni di riferimento per gli ambienti Databricks Data Science & Engineering, Databricks Machine Learning e Databricks SQL.Documentazione AWSDocumentazione AzureDocumentazione GoogleEventi e community di DatabricksConvegno Dati + AIPartecipa per assistere agli interventi, agli annunci di prodotto e a oltre 200 sessioni tecniche, con una schiera di esperti del mondo del lavoro, della ricerca e dell'università.Maggiori informazioniEventi globaliPrenota un posto per una delle nostre conferenze internazionali o regionali, demo di prodotti, webinar, eventi o meetup sponsorizzati dai partner.Maggiori informazioniMeetup online su dati e IAScopri che cosa succede nei Meetup di Databricks in tutto il mondo e unisciti a un gruppo vicino o lontano... tutto virtualmente!Maggiori informazioniBeaconsIncontra i Databricks Beacon, membri selezionati della community che "vanno oltre" per migliorare la community di gestione dei dati e AI.Maggiori informazioniUniversity AllianceUnisciti alla Databricks University Alliance per accedere a risorse complementari per formatori che vogliono insegnare a utilizzare Databricks.Maggiori informazioniVideocast Data BrewEsplorare Dati + AI con gli espertiBrooke Wenig e Denny LeeSerie videoDibattiti tecnici e meetup onlineBrooke Wenig e Denny LeeColloqui tecniciGestire l'intero ciclo di vita del Machine Learning con MLflowJules DamjiColloqui tecniciPrimi passi con Delta LakeDenny LeeColloqui tecniciApprofondimento su Delta Lake (avanzato)Denny LeeDatabricks Demo Hub (dimostrazioni di prodotto)Studio su Dati + IAMatei ZahariaCofondatore e direttore tecnologicodatabricksReynold XinCofondatore e Chief ArchitectdatabricksSue Ann HongIngegnere softwaredatabricksLeggi i documenti più recenti scritti da fondatori, personale e ricercatori di Databricks su sistemi distribuiti, IA e analisi dei dati, in collaborazione con prestigiose università come Berkeley e Stanford.Accesso alla ricercaProdottoPanoramica 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/anna-russo/#
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Anna Russo - 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 ExperiencePricingAnna RussoGlobal Director of Data Science at GucciBack 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/dael-williamson
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Dael Williamson - 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 ExperiencePricingDael WilliamsonField CTO at DatabricksBack to speakersAs the EMEA CTO for Databricks, Dael provides thought leadership and guidance for the C-level executives at major customers. Prior to joining Databricks, Dael was the Global Data Technology Lead at Avanade/Accenture. An entrepreneurial CTO and Business Platform Economist focussed on digital, data & AI led business transformations across different industries. A published data scientist in the field of protein molecular modelling, with extensive experience working in start-ups and enterprises.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/jonathan-hollander
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Jonathan Hollander - 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 ExperiencePricingJonathan HollanderVP, Enterprise Data Technology Platforms at TD BankBack 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/industry-lakehouse-blueprints/blueprints-solution-sheet?itm_data=resources-pathfactory
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Industry Lakehouse Blueprints Solution Sheet
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https://www.databricks.com/solutions/accelerators/transaction-enrichment
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Improving the Customer Experience With Transaction Enrichment | 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 AcceleratorTransaction Enrichment With Merchant ClassificationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebookGet startedAutomate transaction enrichment to better understand your customersThese Solution Accelerators have two purposes. First, it shows how the Lakehouse for Financial Services enables banks, open banking aggregators and payment processors to address the challenge of merchant classification. Second, it shows how to use ML to enrich transaction data with contextual information — including store brand and category for downstream use cases, such as customer segmentation or fraud prevention.Gain new customer insights from contextual informationGet the notebookBuild hyper-personalized experiences with transaction dataGet the notebookResourcesCase studyLearn moreBlogLearn moreeBookLearn moreDeliver innovation faster with Solution Accelerators for popular data and AI use cases across industries. See our full library of solutionsReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights
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https://www.databricks.com/de
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Data Lakehouse-Architektur- und KI-Unternehmen – DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT
Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse.
Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.
Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT
Entdecken Sie das Lakehouse für die Fertigung
Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023
Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWEin Lakehouse als Data Warehouse ist die beste WahlOb Daten, Analytics oder KI:
alles auf einer einzigen PlattformJetzt kostenfrei testenMehr InformationenMit der Lakehouse-Plattform Kosten einsparen und Innovation beschleunigenMehr InformationenEinheitlichEine zentrale Plattform für Ihre Daten – mit konsequenter Governance und verfügbar für alle Analyse- und KI-AnwendungenOffenBasiert auf offenen Standards und bietet Unterstützung für jede Cloud – für eine nahtlose Einbindung in Ihren modernen Daten-StackSkalierbarEffizientes Skalieren mit jeder Workload – von einfachen Datenpipelines bis hin zu massiven LLMsDatengesteuerte Unternehmen, die sich für ein Lakehouse entschieden haben
Alle Kunden anzeigen
Lakehouse führt Ihre Datenteams zusammenDatenmanagement und Data EngineeringDatenerfassung und -management optimierenMit automatisiertem und zuverlässigem ETL, offenem und sicherem Datenaustausch und atemberaubender Leistungsfähigkeit verwandelt Delta Lake Ihren Data Lake in ein Ziel für Ihre gesamten strukturierten, teilstrukturierten und unstrukturierten Daten.Weitere Informationen Demo ansehenData-WarehousingAus vollständigen Daten neue Erkenntnisse gewinnenDurch den direkten Zugriff auf topaktuelle und vollständige Daten und mit der Leistungsfähigkeit von Databricks SQL – mit einem im Vergleich zu traditionellen Cloud-Data-Warehouses bis zu 12-mal besseren Preis-Leistungs-Verhältnis – können Datenanalysten und Data Scientists jetzt im Handumdrehen neue Erkenntnisse gewinnen.Weitere Informationen Demo ansehenData Science und Machine LearningDen gesamten ML-Lifecycle beschleunigenDas Lakehouse bildet die Grundlage von Databricks Machine Learning, einer datennativen und kollaborativen Lösung für den gesamten Machine-Learning-Lebenszyklus von der Featurisierung bis zur Produktion. Kombiniert mit hochwertigen und leistungsstarken Datenpipelines beschleunigt Lakehouse Machine Learning und Produktivität des Teams.Weitere Informationen Demo ansehenDaten-Governance und -TeilenVereinheitlichung von Governance und Teilen für Daten, Analytics und KIMit Databricks erhalten Sie ein gemeinsames Sicherheits- und Governance-Modell für alle Ihre Daten-, Analytics- und KI-Assets im Lakehouse in jeder Cloud. Sie können Daten auf Datenplattformen, Clouds oder Regionen ohne Replikation oder Sperrung finden und teilen sowie Datenprodukte über einen offenen Marketplace verteilen.Weitere Informationen Demo ansehenDas Data Warehouse ist Geschichte. Finden Sie jetzt heraus, warum das Lakehouse in Sachen Architektur für Daten und KI die führende Rolle übernommen hat.Discover LakehouseDer Sessionkatalog ist jetzt onlineSeien Sie in San Francisco dabei, um das Lakehouse-Ökosystem kennenzulernen und sich mit aktuellen Fortschritten bei Open-Source-Technologien vertraut zu machenSessions erkundenErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hat.Bericht abrufen600 CIOs. 14 Branchen. 18 Länder.Diese neue Studie zeigt, dass eine Datenstrategie entscheidend für den KI-Erfolg ist. Erfahren Sie mehr über CIO-Perspektiven.Bericht abrufenPflichtlektüre für ML-Engineers und Data Scientists, die nach einer besseren Methode zur Durchführung von MLOps suchenE-Book herunterladenMöchten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter
„Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte
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https://www.databricks.com/dataaisummit/speaker/chris-hecht/#
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Chris Hecht - 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 Hecht 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/de#yourprivacychoices
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Data Lakehouse-Architektur- und KI-Unternehmen – DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT
Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse.
Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.
Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT
Entdecken Sie das Lakehouse für die Fertigung
Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023
Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWEin Lakehouse als Data Warehouse ist die beste WahlOb Daten, Analytics oder KI:
alles auf einer einzigen PlattformJetzt kostenfrei testenMehr InformationenMit der Lakehouse-Plattform Kosten einsparen und Innovation beschleunigenMehr InformationenEinheitlichEine zentrale Plattform für Ihre Daten – mit konsequenter Governance und verfügbar für alle Analyse- und KI-AnwendungenOffenBasiert auf offenen Standards und bietet Unterstützung für jede Cloud – für eine nahtlose Einbindung in Ihren modernen Daten-StackSkalierbarEffizientes Skalieren mit jeder Workload – von einfachen Datenpipelines bis hin zu massiven LLMsDatengesteuerte Unternehmen, die sich für ein Lakehouse entschieden haben
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Lakehouse führt Ihre Datenteams zusammenDatenmanagement und Data EngineeringDatenerfassung und -management optimierenMit automatisiertem und zuverlässigem ETL, offenem und sicherem Datenaustausch und atemberaubender Leistungsfähigkeit verwandelt Delta Lake Ihren Data Lake in ein Ziel für Ihre gesamten strukturierten, teilstrukturierten und unstrukturierten Daten.Weitere Informationen Demo ansehenData-WarehousingAus vollständigen Daten neue Erkenntnisse gewinnenDurch den direkten Zugriff auf topaktuelle und vollständige Daten und mit der Leistungsfähigkeit von Databricks SQL – mit einem im Vergleich zu traditionellen Cloud-Data-Warehouses bis zu 12-mal besseren Preis-Leistungs-Verhältnis – können Datenanalysten und Data Scientists jetzt im Handumdrehen neue Erkenntnisse gewinnen.Weitere Informationen Demo ansehenData Science und Machine LearningDen gesamten ML-Lifecycle beschleunigenDas Lakehouse bildet die Grundlage von Databricks Machine Learning, einer datennativen und kollaborativen Lösung für den gesamten Machine-Learning-Lebenszyklus von der Featurisierung bis zur Produktion. Kombiniert mit hochwertigen und leistungsstarken Datenpipelines beschleunigt Lakehouse Machine Learning und Produktivität des Teams.Weitere Informationen Demo ansehenDaten-Governance und -TeilenVereinheitlichung von Governance und Teilen für Daten, Analytics und KIMit Databricks erhalten Sie ein gemeinsames Sicherheits- und Governance-Modell für alle Ihre Daten-, Analytics- und KI-Assets im Lakehouse in jeder Cloud. Sie können Daten auf Datenplattformen, Clouds oder Regionen ohne Replikation oder Sperrung finden und teilen sowie Datenprodukte über einen offenen Marketplace verteilen.Weitere Informationen Demo ansehenDas Data Warehouse ist Geschichte. Finden Sie jetzt heraus, warum das Lakehouse in Sachen Architektur für Daten und KI die führende Rolle übernommen hat.Discover LakehouseDer Sessionkatalog ist jetzt onlineSeien Sie in San Francisco dabei, um das Lakehouse-Ökosystem kennenzulernen und sich mit aktuellen Fortschritten bei Open-Source-Technologien vertraut zu machenSessions erkundenErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hat.Bericht abrufen600 CIOs. 14 Branchen. 18 Länder.Diese neue Studie zeigt, dass eine Datenstrategie entscheidend für den KI-Erfolg ist. Erfahren Sie mehr über CIO-Perspektiven.Bericht abrufenPflichtlektüre für ML-Engineers und Data Scientists, die nach einer besseren Methode zur Durchführung von MLOps suchenE-Book herunterladenMöchten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter
„Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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Healthcare 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 NOWDatabricks for the Healthcare IndustryDeliver patient-centric care with the power of data and AIData and AI are revolutionizing how healthcare organizations treat patients and deliver value for the broader population.Databricks empowers healthcare organizations to solve some of their hardest problems by unifying data analytics and machine learning to unlock precision care, improve patient engagement and streamline administration processes.Learn more about the Lakehouse for Healthcare and Life SciencesBest practices for bringing AI into the clinic. Read the ebook.Leading healthcare organizations use Databricks to drive innovation in patient careLatest blog posts, webinars, and case studiesWhy Databricks for healthcareUnlock health data and break data silosConnect structured and unstructured data from EHRs, wearables, imaging platforms, genome sequencers and more to deliver a complete view into patient health.Patient insights at population scaleBetter predict health risks with analytics and AI that scale for millions of patient records in the cloud.Deliver reproducibility and complianceCollaborative analytics workspaces that bring data teams together while streamlining the machine learning lifecycle and providing regulatory-grade MLOps.Use casesAcross the healthcare landscape, data and AI is providing insights and predictive capabilities to personalize care, automate claims and payment processing, and improve patient engagement.Administrative process automationAutomate the analysis of claims and EHR data to streamline administrative workflows.
Claims and revenue cycle automation
Fraud and waste detection
Optimize staffing and operations
Population healthPredict broader health risks by analyzing social, behavioral and environmental factors at scale.
Identify the impact of social determinants of health
Identify and manage undiagnosed chronic disease
Build predictive risk models
Patient engagementOptimize patient care cycles by creating tailored experiences.
Reduce churn through Member 360
Reduce healthcare costs with benefits recommendations
Proactively monitor patient health with digital apps
Learn more about our healthcare solutionsResourcesCase StudiesCVS HealthAustin HealthSanford HealthHealthdirect AustraliaWebinarsDetecting Financial Fraud at Scale with Decision Trees and MLflow on DatabricksImproving Patient Insights With a Modern Clinical Data LakeeBooksUncover New Patient Insights With Natural Language Processing at ScaleAI and Healthcare: Bringing AI Into a Clinical SettingHow HLI Detects Dementia With Deep Learning on Medical ImagesDatabricks for Healthcare Solution SheetReady to get started?We’d love to understand your business goals and how our services team can help you succeed. Try Databricks 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.
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Ifigeneia Derekli - 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 ExperiencePricingIfigeneia DerekliField Engineering Manager & Unity Catalog Specialist at DatabricksBack to speakersField Engineering Manager at 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/company/partners/consulting-and-si/partner-solutions/deloitte-precisionview
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PrecisionView™ for HLS by Deloitte and Databricks | 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 SolutionPrecisionViewTM by Deloitte
Industry-specific solution developed by Deloitte and powered by the Databricks Lakehouse Platform
Get startedExpand capabilities, increase capacity and enrich internal collaboration for the finance organizationPrecisionView™, Deloitte's proprietary advanced forecasting solution for healthcare and life sciences, leverages data aggregation technologies with predictive analytics as well as cognitive and machine-learning capabilities to let businesses generate improved forecasting accuracy and predictive modeling. The solution also helps generate high-impact insights that relate to the total enterprise, business units, geographies and products. It's no secret that traditional forecasting and predictive modeling methods can be excessively manual and prone to unintentional human bias or sandbagging. PrecisionView, plus the right user experience, can help change that by:Improving business and investment decision-making powered by scenario analysisIdentifying influential business drivers and modeling key business leversDecreasing time-to-insight and enhancing the delivery of financial insights and visualsGet 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
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技術パートナー | DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT
さようなら、データウェアハウス。こんにちは、レイクハウス。
データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。
今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)
製造業のためのレイクハウスを発見する
コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日
直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOW技術パートナー技術パートナーとの連携により、データブリックスのレイクハウスプラットフォームにおけるデータの取り込み、BI、ガバナンスのためのケイパビリティを強化します。「Databricks と Fivetran の技術連携により、マーケティングインサイトの大幅な向上が期待できます。技術の面でも、この 2 つのツールは調和して作用し、まるでネイティブな統合です。」Paul Hewitt 社 BI & ERP チームリーダー Jan-Niklas Mühlenbrock 氏データブリックスの技術パートナーは、ソリューションをデータブリックスと統合し、ETL、データの取り込み、BI、機械学習、ガバナンスのためのケイパビリティを高めます。このパートナーシップにより、お客様における高い信頼性とスケーラビリティを備えたデータブリックスのレイクハウスプラットフォームの活用、イノベーションの加速、データドリブンな気づきの抽出が可能になります。Partner Connectデータ、分析、AI ツールを単一のオープンプラットフォームに集約できます。Partner Connect により、Databricks 認証済みの統合機能を使用して既存のツールを迅速かつ容易にレイクハウスに接続でき、新たなソリューションの発見と試行が促進されます 。パートナーになる詳しく見るLoading...製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆イ ンクルージョンDatabricks ブログご相談・お問い合わせ 採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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Databricks University Alliance for Aspiring Data Scientists | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT
Goodbye, Data Warehouse. Hello, Lakehouse.
Attend to understand how a data lakehouse fits within your modern data stack.
Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence.
See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco
June 26–29
Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWUniversity AllianceResources and materials for educators, students and aspiring data scientists who want to build with DatabricksJoin as an educatorI'm a studentAt Databricks, we believe that university students should learn the latest data science tools to enhance their value in the workforce upon graduation. The Databricks University Alliance provides complimentary assets to educators and students for teaching and learning these next-generation tools in both in-person and virtual classrooms.All approved educators and faculty receive:Access to the online community of educators using Databricks in the classroomA curated list of resources for educators getting started with Databricks, including slides and workshops on topics like Delta Lake and Apache Spark™Sample notebooks to jump-start the learning experience for Delta Lake, MLflow and moreBrowse notebooksSelect classes needing high-scale computing resources may request free Databricks credits and cloud credits for courses powered by AWS and Azure (limited availability)Interested in teaching Databricks?If you’re an educator or faculty member at a university, you are invited to join the Databricks University Alliance.Join now“Having access to industry-leading tools and programs provided by Databricks, a company that continues to drive innovation across the data science and machine learning community, is very exciting for our professors, students and university.”— Kyle Hamilton, professor and coordinator of the Machine Learning at Scale course at UC BerkeleyAre you a student or aspiring data scientist?You don’t need to wait to start learning Databricks. Check out the resources available to you right now.Learning seriesHands-on workshopsThis self-paced online workshop series is for anyone and everyone interested in learning about data analysis. No previous programming experience required.Learn moreDatabricks accountSign up for the Databricks Community EditionSign up for a free Databricks account to follow along with tutorials and experiment with data.Sign up freeDatabricks AcademyAccess free self-paced courses on DatabricksIf you’re a student with a university-provided email address, you can access courses on Databricks Academy free.See detailsOur cloud partners
ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. 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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Lösungen für Medien und Unterhaltung – Databricks Lakehouse – DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT
Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse.
Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.
Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT
Entdecken Sie das Lakehouse für die Fertigung
Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023
Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWDatabricks für Medien und UnterhaltungDie Zukunft der Medien ist daten-, analyse- und KI-gestützt – und Sie können dabei seinErste SchrittePlanen Sie eine DemoVier Herausforderungen in der Medien- und UnterhaltungsbrancheErstellen eines einheitlichen Zielgruppenprofils
Daten, die in unterschiedlichen Systemen erfasst, gespeichert und verwaltet werden, verhindern, dass Medienunternehmen einen vollständigen Überblick über Zuschauer- und Werbedaten haben.Optimiertes Benutzererlebnis vermitteln
Ganz gleich, welches Gerät sie nutzen: Verbraucher erwarten jederzeit reibungslose, personalisierte 1:1-Erlebnisse. Für Sie besteht die Herausforderung darin, solche Erlebnisse in Echtzeit und umfassend bereitzustellen.Maximieren aller Mediendaten
Veraltete Data Warehouses können unstrukturierte Daten wie Video-, Bild- und Audiodateien nicht verarbeiten. So werden Unternehmen daran gehindert, das Potenzial ihrer wertvollsten Ressourcen zu erschließen.Über die Aggregation hinaus zu fortgeschrittener Analytics
Komplexe KI-Anwendungsfälle für den Werbe- und Verbraucherlebenszyklus erfordern derzeit die teure Erfassung und Harmonisierung riesiger Datensätze.Data Lakehouse – das Beste aus beiden Welten auf einer einzigen PlattformEin Data Lakehouse führt das Beste aus Data Warehouse und Data Lake auf einer einzigen einfachen Plattform zusammen, mit der Sie alle Ihre Anwendungsfälle aus den Bereichen Daten, Analytics und KI bewältigen. Es setzt dabei auf eine offene und zuverlässige Datenbasis auf, die alle Datentypen effizient verarbeitet und einen gemeinsamen Sicherheits- und Governance-Ansatz auf alle Ihre Daten- und Cloud-Plattformen anwendet.Mehr InformationenDas Lakehouse in AktionSo stärkt das Databricks Lakehouse auch Ihre Branche maßgeschneidertWerbe- und MarketingtechnologienVerwalten Sie Margen, setzen Sie auf Grundlage Ihrer Daten maximale Präzision im Betrieb durch, steigern Sie die Medienleistung und optimieren Sie Werbemittel – all dies, um die Arbeit für Ihre Teams zu verbessern.Mehr InformationenRundfunk und StreamingErstellen Sie breit gefächerte, personalisierte 1:1-Erlebnisse, verbessern Sie die Werbeleistung und -optimierung und steigern Sie den Mehrwert Ihres gesamten Content-Portfolios.Mehr InformationenGamingNutzen Sie Daten und KI, um die Spieleentwicklung zu verbessern, mehr Spieler zu finden und zu binden und Monetarisierung und Bindung von Spielern zu stärken.Mehr InformationenWarum Databricks für Medien und Unterhaltung?Ob Daten, Analytics oder KI: alles auf einer einzigen Plattform
Erschließen Sie das gesamte Potenzial Ihrer Daten, um bei Zielgruppeninteraktion, Monetarisierung und Werbeoptimierung bahnbrechende Ergebnisse zu erzielen.Optimiert für die Echtzeitverarbeitung
Entdecken Sie umsetzbare Erkenntnisse, fördern Sie die 1:1-Personalisierung und verbessern Sie das Nutzungserlebnis Ihrer Zielgruppe auf Grundlage von maschinellem Lernen.Ihre Geschäftsergebnisse beschleunigen
Nutzen Sie Solution Accelerators, mit denen das Erfassen von Verbraucherdaten (z. B. Clickstream-Interaktionen) und das Bereitstellen von Anwendungsfällen wie Empfehlungs-Engines und Multi-Touch-Attribution zum Kinderspiel wird.Maximale Zuverlässigkeit und Leistung
Mit dem Databricks Lakehouse setzen Sie beispiellose Optimierungen bei Skalierung, Geschwindigkeit und Kosten um. Deswegen ist es auch nicht verwunderlich, dass das beste Data Warehouse ein Lakehouse ist.Transformation für die Medien- und Unterhaltungsbranche – mit dem Lakehouse
„Mit der Lakehouse-Plattform von Databricks auf AWS hat Warner Bros. Discovery die Zukunft von Content Discovery und Zuschauererlebnissen neu erfunden. Durch die Nutzung von Daten zur besseren Vorhersage des Verbraucherverhaltens und zur Bereitstellung personalisierter Inhaltsempfehlungen in Echtzeit sind wir in der Lage, das Zuschauererlebnis individuell zu gestalten und die Einbindung unserer Kunden insgesamt zu verbessern.“– Martin Ma, GVP, Engineering bei Warner Bros. DiscoveryErkenntnisse von Führungskräften zu Daten, Analytics und KIErfahren Sie mehr darüber, was andere Führungskräfte aus der Medien- und Unterhaltungsbranche tun, um ihre Datenstrategie umzusetzenMehr InformationenWas kann man mit dem Lakehouse machen?
Schnellere Ergebnisse für Zielgruppen und Werbetreibende – dank einer offenen, kollaborativen Plattform für Daten, Analytics und KI360°-Blick auf Ihr Publikum
Führen Sie all Ihre strukturierten und unstrukturierten Daten, z. B. Clickstream, demografische und soziale Daten, in einer einzigen Plattform für Analytics und KI zusammen. Mit einer ganzheitlichen Sicht auf die Customer Journey können Unternehmen die Vorlieben für Inhalte verstehen, die zu personalisierteren Erlebnissen und der Entwicklung zielgerichteter Werbung und Interaktion beitragen.Reduzieren der Abwanderung und Erhöhen des durchschnittlichen Ertrags pro Nutzer
Mit einer flexiblen, cloudbasierten Plattform können Unternehmen schnell und zuverlässig riesige Datenmengen verarbeiten und an nachgelagerte Systeme weiterleiten, um auf jedem Kanal und zu jeder Zeit ein 1:1-Erlebnis zu bieten. Da die Erwartungen der Verbraucher in Bezug auf Echtzeit-Empfehlungen immer weiter steigen und Medienunternehmen um die Aufmerksamkeit der Verbraucher kämpfen, wird es für viele Unternehmen zur Pflicht, eine Personalisierung in Echtzeit zu gewährleisten.Steigern des Umsatzes durch eine Inhaltsbibliothek
Medienunternehmen setzen auf unstrukturierte Daten wie Video-, Bild- und Audiodateien. Daher ist die Fähigkeit, solche Daten zu analysieren, für ein effektives Media Asset Management unerlässlich. Mit Lakehouse for M&E können Marketer archivierte Inhalte für Kampagnen nutzen, Produktionsteams vorhandene Inhalte für neue Produktionen finden und Vertriebsteams selbst erstelltes Material an andere Medienunternehmen verkaufen.Einsatzfertige Modelle für ML/KI nutzen und ML in den Mittelpunkt Ihres Unternehmens stellen
Nutzen Sie die Möglichkeiten des Machine Learnings, um die Bedürfnisse von Verbrauchern, Mitarbeitern und Werbetreibenden besser zu verstehen. Wenn alle Ihre Daten zentralisiert und nahtlos durch eine umfassende Suite von kollaborativen Analytics- und Machine Learning-Tools verbunden sind, können Datenteams zusammenarbeiten, um leistungsstarke Prognosemodelle zu entwickeln, die neue Innovationen in den Bereichen Personalisierung, Monetarisierung von Inhalten und Werbeergebnisse vorantreiben.E-Book herunterladenPartner und Lösungen
Jede Menge gebrauchsfertige Daten- und Analytics-Lösungen und -Vorlagen speziell für Medien und Unterhaltung
Unser Partnerportal erkundenMulti-Touch-ZuordnungMessen der Werbewirksamkeit und Optimieren Ihrer Marketingausgaben mit einer besseren KanalzuordnungErste SchritteToxizität von Spielern/NutzernFördern problemfreierer Nutzergemeinschaften durch Echtzeit-Erkennung von toxischer Sprache und toxischem VerhaltenErste SchritteÜberlebensanalyse/LTVVorhersagen, welche Verbraucher abwanderungsgefährdet sind und welche Faktoren den Lebenszyklus der Verbraucher verlängernErste SchritteNeigung zur AbwanderungEffektives Verwalten der Kundenbindung, Verstehen des Lebenszyklus und Reduzieren der AbwanderungsrateErste SchritteVerhaltensorientierte SegmentierungErstellen erweiterter Segmente, um bessere Einkaufsprognosen basierend auf Verhaltensweisen zu erzielenErste SchritteAbsatzprognosen und -zuordnungSteigern der Werbeergebnisse durch Optimierung und Konzentration auf die leistungsstärksten KanäleErste SchritteEmpfehlungenSteigern von Konversionen und Einbindung mit personalisierten Omnichannel-EmpfehlungenErste SchritteComputer Vision/LabelboxKommentieren von Bildern und Videos, um die kontextbezogene Anzeigenausrichtung im Lakehouse zu unterstützen
In Kürze verfügbarVideo Quality of ExperienceAnalysieren von Batch- und Streaming-Daten, um ein leistungsfähiges Streaming-Inhaltserlebnis zu gewährleistenErste SchritteReal-Time BiddingErfahren, wie Sie die Sichtbarkeit von Anzeigen in Echtzeit vorhersagen können, um Ihre RTB-Strategie zu verbessernErste SchritteAlle Lösungen anzeigenLakehouse für Medien und Unterhaltung in der PraxisRessourcen
Alle Ressourcen, die Sie brauchen. Alle an einem Ort.
In der Ressourcenbibliothek finden Sie E-Books und Videos zu Daten und KI für die Medien- und Unterhaltungsbranche.
Ressourcen erkundenE-BookJETZT HERUNTERLADENWebinareMehr InformationenBlogsMehr InformationenMöchten Sie loslegen?Wir würden uns freuen, Ihre Geschäftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENPlanen Sie eine DemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter
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Ali Ghodsi - 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 ExperiencePricingAli GhodsiCo-founder and CEO at DatabricksBack to speakersAli Ghodsi, the CEO and co-founder of Databricks, is responsible for the growth and international expansion of the company. He previously served as the VP of Engineering and Product Management before taking the role of CEO in January 2016. In addition to his work at Databricks, Ali serves as an adjunct professor at UC Berkeley and is on the board at UC Berkeley’s RISELab. Ali was one of the original creators of the open source project, Apache Spark, and ideas from his academic research in the areas of resource management and scheduling and data caching have been applied to Apache Mesos and Apache Hadoop. Ali received his MBA from Mid-Sweden University in 2003 and a Ph.D. from KTH/Royal Institute of Technology in Sweden in 2006 in the area of Distributed Computing.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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Databricks ソリューションアクセラレータ – データ分析と AI による価値創出を加速 | DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT
さようなら、データウェアハウス。こんにちは、レイクハウス。
データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。
今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)
製造業のためのレイクハウスを発見する
コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日
直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOW業種別ソリューションデータと AI の成果を加速無料トライアルDatabricks ソリューションアクセラレータDatabricks ソリューションアクセラレータは、さまざまな業界・業種に共通の主要なユースケースに対応する、フル機能の Notebook やベストプラクティスを含む目的に特化したガイドです。ソリューションアクセラレータを使用することで、発見、設計、開発、テストにかかる時間を短縮できます。発案から PoC までを 2 週間以内に完了できるよう設計されています。
ソリューションアクセラレータは、Databricks の無料トライアルへのご登録、または既存のアカウントで使用できます。
無料トライアルアクセラレータを検索searchHide filtersIndustrySortDatabricks高粒度で大規模な需要予測featured🔥Databricks店頭在庫管理featuredDatabricksゲームにおける有害性の検知featuredDatabricksPHI 除去の自動化featurednewDatabricksdbigniteによるFHIR相互運用性DatabricksDNS による脅威検知DatabricksESG 指標分析🔥DatabricksR&D 知識グラフによる最適化newDatabricksSmolderによるHL7v2相互運用性DatabricksアンチマネーロンダリングDatabricksオーダーピッキングの最適化Databricksカスタマーエントリーの解決Databricksゲノムワイド関連解析Databricksコンピュータビジョンの基礎Splunkサイバーアナリティクス（Splunkコネクタ）Databricksサブスクリプションの解約予測Databricksスケーラブルなルート生成DatabricksデジタルツインDatabricksデジタル病理画像の解析Databricksナレッジグラフを用いたコホート構築DatabricksファジーアイテムマッチングDatabricksマーチャント分類Databricksマルチタッチ広告のアトリビューションDatabricksメディケア・リスク・アジャストメントDatabricksモダン投資データプラットフォームDatabricksリアルタイム POS 分析newDatabricksリアルタイムな金融不正防止Databricksリアルタイム入札の最適化DatabricksリアルワールドエビデンスDatabricksリスク管理Databricksリテンション管理DatabricksレピュテーションリスクDatabricks予測型メンテナンス（IoT）Databricks価格の透明性newDatabricks健康の社会的決定要因Databricks傾向スコアリングnewDatabricks動画配信の体験品質（QoE）Databricks地理空間分析による ID 不正の特定Databricks売上予測と広告アトリビューション🔥Databricks安全在庫Databricks推薦エンジンDatabricks有害事象の検出newDatabricks生存時間分析と生涯価値Databricks腫瘍学のためのリアルワールドデータの抽象化Databricks規制報告書Databricks設備総合効率（ OEE )Databricks顧客セグメンテーションDatabricks顧客の生涯価値🔥よくある質問ソリューションアクセラレータの料金は？Databricks のお客様は、ソリューションアクセラレータを無料で利用できます。ソリューションアクセラレータを使用するには、Databricks ユーザーである必要がありますか？ソリューションアクセラレータの使用には、Databricks 無料トライアルへのご登録、または既存の Databricks アカウントが必要です。ソリューションアクセラレータのメリットは？ソリューションアクセラレータを使用することで、発見、設計、開発、テストにかかる時間を短縮できます。Notebook や実証済みのパターン、ベストプラクティスといったリソースを活用し、データと AI のユースケースをすぐに展開できるように設計されています。発案から PoC までを最短 2 週間で完了できます。Databricks 導入事例のご紹介導入事例を見る製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ 採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
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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.プライバシー通知|利用規約|プライバシー設定|カリフォルニア州のプライバシー権利
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Michael Armbrust - 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 ArmbrustDistinguished Engineer at DatabricksBack to speakersMichael Armbrust is committer and PMC member of Apache Spark™ and the original creator of Spark SQL. He currently leads the Delta Live Tables team at Databricks and is the original creator of Spark SQL, Structured Streaming and Delta. He received his PhD from UC Berkeley in 2013, and was advised by Michael Franklin, David Patterson, and Armando Fox. His thesis focused on building systems that allow developers to rapidly build scalable interactive applications, and specifically defined the notion of scale independence. His interests broadly include distributed systems, large-scale structured storage and query optimization.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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Migrate your data warehouse to 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 NOWMigrate your data warehouse to DatabricksBecause the best data warehouse is a lakehouse
Try Databricks freeContact DatabricksLegacy data warehouses are costly to maintain, unscalable and cannot deliver on data science, ML and real-time analytics use cases. Migrating from your enterprise data warehouse to Databricks lets you scale as your business needs grow and accelerate innovation by running all your data, analytics and AI workloads on a single unified data platform.The case for modernizing your enterprise data warehouseEnterprise data warehouses have traditionally supported only historical reporting — with no support for forward-looking prescriptive and predictive analytics. They also cannot handle semi-structured, unstructured or real-time data and are not set up for advanced analytics use cases that data science teams need to drive ML and AI–powered innovations. If that wasn’t enough, EDWs store data in closed proprietary formats, impose rigid vendor lock-ins and are prohibitively expensive to scale.Read this TDWI report on how you can overcome these challenges by transitioning from a data warehouse to a data lakehouse.
The Wisdom of Transitioning to a Data Lakehouse Strategy
How a data lakehouse approach can help you overcome the common limitations of data warehouses and data lakes
Download nowWhy migrate your data warehouse to the Databricks Lakehouse?Simplify your data platform
Get a single modern platform for all your data, analytics and AI use cases. Unify governance and the user experience across clouds and data teams.
Scale cost-effectively
Stop managing servers, and scale on demand with serverless. Run data warehousing at scale with up to 12x better price/performance.
Accelerate innovation
Build AI, ML and real-time analytics capabilities faster with collaborative, self-service tools and open source technologies such as MLflow and Apache Spark™.
Migrate with confidence
Automated tools, technical guidance, partner solutions and professional services help you eliminate risk and accelerate your migration journey.
Technical guidance for data migration, ETL and code migration, and BI reportingData MigrationPull data into Databricks from various database sourcesPush data out from EDWs to cloud storage and use Databricks AutoLoaderUse our ingestion partners such as Fivetran, Qlik Replicate and Arcion from Databricks Partner ConnectETL and Code MigrationBI ReportingReady to take your first step?Contact DatabricksMigration resourcesWebinarModernize Your Data Warehouse
Watch noweBookMigrating From a Data Warehouse to a Data Lakehouse for Dummies
Download nowMigration GuideStrategies to Evolve Your Data Warehouse to the Databricks Lakehouse
Download nowBrickbuilder SolutionsLeverage Brickbuilder Solutions from leading consulting partners — built for migrating your data warehouse to the Databricks LakehouseLegacy System Migration by AvanadeMove your data to unlock its full value
Get startedMigrate to Cloud and Databricks by CapgeminiStreamline data migration to the Databricks Lakehouse Platform
Get startedMigrate to Databricks by Celebal TechnologiesQuicker migration from on-premises at lower cost
Get startedLeapLogic Migration Solution by ImpetusAuto-transform ETL, data warehouse, analytics and Hadoop workloads to Databricks
Get startedData Wizard for Hadoop/EDW Migrations by InfosysConfidently move your data to Databricks
Get startedSnowflake-to-Databricks Migration by LovelyticsEnsure a rapid and sound migration process
Get startedSAS Migration Accelerator by Tensile AIMigration solution developed by Tensile AI and powered by the Databricks Lakehouse Platform
Get startedData Intelligence Suite by WiproMigrate with confidence to Databricks
Get startedCustomers who have successfully migrated their data warehouse to DatabricksMigrating from Hadoop?Learn moreResourceseBooksWhy the Data Lakehouse Is Your Next Data WarehouseMigrating From a Data Warehouse to a Data Lakehouse for DummiesStrategies to Evolve Your Data Warehouse to the Databricks LakehouseEventsModernize Your Data WarehouseHow to Automate the Modernization and Migration of Your Data Warehousing Workloads to Databricks LakehouseData Transformation in the Lakehouse Made Simple With Fivetran and DatabricksTableau Unleashed With a Data LakehouseLeapLogic — A Cloud Accelerator for Transformation of Legacy Analytics, ETL, DW and HadoopBlogsData Warehousing Modeling Techniques and Their Implementation on the Databricks Lakehouse PlatformPrescriptive Guidance for Implementing a Data Vault Model on the Databricks Lakehouse PlatformFive Simple Steps for Implementing a Star Schema in Databricks With Delta LakeDimensional Modeling Best Practices and Implementation on a Modern LakehouseGet startedMigration doesn’t have to be a headache. Contact us today to talk about what it could look like for you.Try Databricks freeContact DatabricksProductPlatform 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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データ+AI サミット 2023 - 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 ExperiencePricing2023年6月26～29日（米国時間）データ+AI サミット 2023データ、分析、AI コミュニティのためのグローバルイベントご登録米国時間 6月26日～29日於サンフランシスコ：
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Databricks の無料トライアル | DatabricksDatabricks の無料トライアルDatabricks プラットフォームの全機能を 14 日間無料でお試しいただけます。AWS、Microsoft Azure、Google Cloud のいずれかをお選びください。データの取り込みをシンプルに、ETL を自動化数百におよぶソースからのデータの取り込みと、シンプルな宣言型アプローチによるデータパイプラインの構築を可能にします。任意の言語でコラボレーションを促進Python、R、Scala、SQL によるコーディングが可能です。共同編集、自動バージョン管理、Git 統合、RBAC も利用できます。クラウドデータウェアハウスの 12 倍の価格性能Databricks は、世界 7000 社以上のお客様に採用され、BI や AI のあらゆるワークロードをサポートしています。Databricks アカウントを作成する1/2お名前（姓)お名前（名)業務用メールアドレス企業／団体名役職名電話番号（任意)選択してください国名送信プライバシー通知 (更新)利用規約プライバシー設定カリフォルニア州のプライバシー権利
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https://www.databricks.com/dataaisummit/speaker/megan-fogal/#
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Megan Fogal - 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 ExperiencePricingMegan FogalSolutions Architect 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/dataaisummit/speaker/pritesh-patel/#
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Pritesh 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 ExperiencePricingPritesh PatelPublic Sector Leader, UK&I at DatabricksBack to speakersSales leader with years of experience in Public Sector and with passion to deliver citizen and social value through data and AI.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/streaming-analytics
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What is Streaming Analytics?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 NOWStreaming AnalyticsAll>Streaming AnalyticsHow Does Stream Analytics Work?Streaming analytics, also known as event stream processing, is the analysis of huge pools of current and “in-motion” data through the use of continuous queries, called event streams. These streams are triggered by a specific event that happens as a direct result of an action or set of actions, like a financial transaction, equipment failure, a social post or a website click or some other measurable activity. The data can originate from the Internet of Things (IoT), transactions, cloud applications, web interactions, mobile devices, and machine sensors. By using streaming analytics platforms organizations can extract business value from data in motion just like traditional analytics tools would allow them to do with data at rest. Real-time streaming analytics help a range of industries by spotting opportunities and risks.The Advantages of Streaming AnalyticsData visualization. Keeping an eye on the most important company information can help organizations manage their key performance indicators (KPIs) on a daily basis. Streaming data can be monitored in real time allowing companies to know what is occurring at every single momentBusiness insights. In case an out of the ordinary business event occurs, it will first show up in the relevant dashboard. It can be used in cybersecurity, to automate detection and response to the threat itself. This is an area where abnormal behavior should be flagged for investigation right away.Increased competitiveness. Businesses looking to gain a competitive advantage can use streaming data to discern trends and set benchmarks faster. This way they can outpace their competitors who are still using the sluggish process of batch analysis.Cutting preventable losses. With the help of streaming analytics, we can prevent or at least reduce the damage of incidents like security breaches, manufacturing issues, customer churn, stock exchange meltdowns, and social media crisis.Analyzing routine business operations. Streaming analytics offers organizations an opportunity to ingest and obtain an instant insight from the real-time data that is pouring in.Your company will be able to answer questions like:How many customers do you have in your store at this very moment, and what are they most likely to purchase?Which vehicles in our fleet are using the most fuel and why?Is there a machinery in your factory that could fail in the next five business days, and what spare parts will be required to keep it running?Your company can now monitor in real time: manufacturing closed-loop control systems; the health of a network or a system; field assets such as trucks, oil rigs, vending machines; and financial transactions such as authentications and validations.Finding missed opportunities. The streaming and analyzing of Big Data can help companies to uncover hidden patterns, correlations and other insights. Companies can get answers from it almost immediately being able to upsell, and cross-sell clients based on what the information presents.Create new opportunities. The existence of streaming data technology brings the type of predictability that cuts costs, solves problems and grows sales. It has led to the invention of new business models, product innovations, and revenue streams.Streaming Analytics with Azure DatabricksTo play this video, click here and accept cookiesAdditional ResourcesSimplifying Streaming Analytics with Delta Lake and Spark WebinarStreaming Analytics with Spark, Kafka, Cassandra, and AkkaGet High-Performance Streaming Analytics with Azure DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
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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/samrat-ray
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Samrat Ray - 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 ExperiencePricingSamrat RaySenior 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/what-are-continuous-applications
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What are Continuous Applications?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 NOWContinuous ApplicationsAll>Continuous ApplicationsTry Databricks for freeGet StartedContinuous applications are an end-to-end application that reacts to data in real-time. In particular, developers would like to use a single programming interface to support the facets of continuous applications that are currently handled in separate systems, such as query serving or interaction with batch jobs. Below is an example of continuous applications can handle the following use cases.Updating data that will be served in real time. The developer would write a single Spark application that handles both updates and serving (e.g. through Spark’s JDBC server), or would use an API that automatically performs transactional updates on a serving system like MySQL, Redis or Apache Cassandra.Extract, transform and load (ETL). The developer would simply list the transformations required as in a batch job, and the streaming system would handle coordination with both storage systems to ensure exactly-once processing.Creating a real-time version of an existing batch job. The streaming system would guarantee results are always consistent with a batch job on the same data.Online machine learning. The machine learning library would be designed to combine real-time training, periodic batch training, and prediction serving behind the same API.Additional ResourcesWriting Continuous Applications with Structured Streaming PySpark APIHeadaches and Breakthroughs in Building Continuous ApplicationsContinuous Applications at Scale of 100 Teams with Databricks Delta and Structured StreamingBack 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/karthik-ramasamy
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Karthik Ramasamy - 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 ExperiencePricingKarthik RamasamyHead of Streaming at DatabricksBack to speakersKarthik Ramasamy is the Head of Streaming at Databricks. Before joining Databricks, he was a Senior Director of Engineering, managing the Pulsar team at Splunk. Before Splunk, he was the co-founder and CEO of Streamlio that focused on building next-generation event processing infrastructure using Apache Pulsar and led the acquisition of Streamlio by Splunk. Before Streamlio, he was the engineering manager and technical lead for real-time infrastructure at Twitter where he co-created Twitter Heron, which was open sourced and used by several companies. He has two decades of experience working with companies such as Teradata, Greenplum and Juniper in their rapid growth stages building parallel databases, big data infrastructure and networking. He co-founded Locomatix, a company that specializes in real-time streaming processing on Hadoop and Cassandra using SQL, which was acquired by Twitter. Karthik has a Ph.D. in computer science from the University of Wisconsin, Madison, with a focus on big data and databases. During his college tenure, several of the research projects he participated in were later spun off as a company acquired by Teradata. Karthik is the author of several publications, patents and a popular book, Network Routing: Algorithms, Protocols and 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/glossary/what-is-machine-learning-library
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What is a Machine Learning Library (MLlib)?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 NOWMachine Learning Library (MLlib)All>Machine Learning Library (MLlib)Try Databricks for freeGet StartedApache Spark’s Machine Learning Library (MLlib) is designed for simplicity, scalability, and easy integration with other tools. With the scalability, language compatibility, and speed of Spark, data scientists can focus on their data problems and models instead of solving the complexities surrounding distributed data (such as infrastructure, configurations, and so on). Built on top of Spark, MLlib is a scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, and underlying optimization primitives. Spark MLLib seamlessly integrates with other Spark components such as Spark SQL, Spark Streaming, and DataFrames and is installed in the Databricks runtime. The library is usable in Java, Scala, and Python as part of Spark applications, so that you can include it in complete workflows. MLlib allows for preprocessing, munging, training of models, and making predictions at scale on data. You can even use models trained in MLlib to make predictions in Structured Streaming. Spark provides a sophisticated machine learning API for performing a variety of machine learning tasks, from classification to regression, clustering to deep learning.Additional ResourcesManaged MLflow ProductGartner names Databricks a Magic Quadrant Leader in Data Science and Machine Learning PlatformsMoving a Fraud-Fighting Random Forest from scikit-learn to Spark with MLlib, MLflow, and JupyterPractical ML | Virtual EventFree Training: Building and Deploying Machine Learning ModelsBack 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/lakhan-prajapati
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Lakhan Prajapati - 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 ExperiencePricingLakhan PrajapatiDirector of Architecture and Engineering at ZS associatesBack to speakersTechnology Enthusiast, Loves solving complex tech problems for the enterprise. Expertise in the field of cloud, data warehousing, and enterprise architectureLooking 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/rahul-pandey
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Rahul Pandey - 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 ExperiencePricingRahul PandeySolution Architect at adidasBack to speakersRahul is working on Data Engineering and Data Science projects as a Solution Architect at Adidas. His goal is to build cost-effective and efficient architecture designs. He is motivated to raise awareness about sustainability in AI within Data Science teams.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/jp/solutions/migration
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Databricks ソリューションへの移行 | DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT
さようなら、データウェアハウス。こんにちは、レイクハウス。
データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。
今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)
製造業のためのレイクハウスを発見する
コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日
直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOWDatabricks ソリューションへの移行Databricks レイクハウスに移行してデータプラットフォームをモダナイズ
Databricks 無料トライアルDatabricks へのお問い合わせエンタープライズのデータウェアハウス、または既存のデータレイクをDatabricks レイクハウスに移行することで、コスト削減、イノベーションの加速、データプラットフォ ームの簡素化が実現します。オープンスタンダードに基づいて構築され、共通のガバナンスアプローチで保護されたモダン統合プラットフォームが、データ、分析、AI のあらゆるワークロードの実行を可能にします。Databricks に移行する理由シンプルなデータプラットフォームデータ、分析、AI のあらゆるユースケースに対応する単一のモダンプラットフォームで、複数のクラウドやデータチーム間のガバナンスとユーザーエクスペリエンスを統合できます。
費用対効果に優れたスケーリングサーバーの管理を不要にし、サーバーレスでオンデマンドに拡張します。データウェアハウスを最大 12 倍の価格性能で実行できます。
イノベーションを加速コラボレーション、セルフサービスツール、MLflow や Apache Spark™ などのオープンソーステクノロジーにより、AI、ML、リアルタイム分析機能を迅速に構築できます。
Hadoop からの移行
詳しく見るデータウェアハウスからの移行
詳しく見る信頼性の高い移行私たちは、何百ものお客さまがレガシーデータプラットフォームから移行するのを支援してきました。段段階的なエンドツーエンドの移行プロセスを使用することで、移行中と移行後のコストを理解するための予測可能なモデルが提供されます。また、レイクハウスファーストのアプローチであらゆるワークロードを移行することで、既存のユースケースだけでなく、新しいユースケースもサポートします。その結果、リスクの低減、価値実現の迅速化、ROIの向上が実現します。データ移行の 5 つのフェーズフェーズ 1：ディスカバリー
プロファイラを使用してディスカバリーを自動化します。レガシープラットフォームのワークロードを把握し、Databricks プラットフォームの消費コストを見積もることができます。
フェーズ 2：アセスメント
コードの複雑さを詳細に評価し、移行プロジェクトのコストを見積もるためにアナライザーを使用します。
フェーズ 3：戦略
Databricks の専門家による指導のもと、テクノロジーマッピングを確定し、各ソースプラットフォームの移行に最適な経路を構築します。
フェーズ 4：生産パイロット
ユースケースを用いたパイロットを実施し、レガシーコードを Databricks 互換のコードに変換するためにコードコンバータを使用します（該当する場合）。マイグレーション実施計画およびロードマップを作成します。
フェーズ 5：処理の実行
すべてのワークロードについて、繰り返し実行します。マイグレーションの実行とサポートについては、認定パートナーまたは Databricks プロフェッショナルサービスから支援を受けることができます。
Databricks への移行を成功させたお客さま導入事例パーソナライズによる患者アウトカムの改善
もっと読むお客様によるブログオンプレミスを完全に廃止し、コスト削減と成果創出の加速を実現
もっと読む導入事例データドリブンなリテールの新時代をクラウドで
もっと読むBrickbuilder SolutionsDatabricks レイクハウスへの移行のために構築された、大手コンサルティングパートナーによる Brickbuilder ソリューションを活用アクセンチュア：クラウドデータマイグレーション推測を減らし、価値を高める
無料トライアルAvanade：レガシーシステムのマイグレーションデータを移動して、価値を最大限に引き出す
無料トライアルCapgemini：クラウドと Databricks への移行Databricks レイクハウスプラットフォームへのデータ移行を効率化
無料トライアルCelebal Technologies：Databricks への移行オンプレミスからの迅速な移行を低コストで実現
無料トライアルImpetus：LeapLogic マイグレーションソリューションETL、データウェアハウス、分析、Hadoop のワークロードを Databricks に自動変換します。
無料トライアルInfosys：Hadoop/EDW マイグレーションのためのデータウィザードDatabricks へのデータ移行に信頼性をもたらす
無料トライアルLovelytics：Snowflake から Databricks への移行迅速かつ健全な移行プロセスを確保する
無料トライアルTensile AI：SAS マイグレーションアクセラレータTensile AI が開発し、Databricks レイクハウスプラットフォームが搭載された移行ソリューション無料トライアルWipro：データインテリジェンススイー トDatabricks への移行を安心して行う
無料トライアルデータレイクハウス戦略への移行の知恵データレイクハウスのアプローチは、データウェアハウスとデータレイクの共通の制限をどのように克服することができるのかダウンロード関連リソースeBook「Hadoop からデータレイクハウスへの移行」入門編データウェアハウスからデータレイクハウスへの移行イベントHadoop から Databricks への移行ガイドデータウェアハウスをモダナイズブログHadoop からレイクハウスへの移行：成功のための 5 つのステップクラウドベースの Hadoop から Databricks レイクハウスプラットフォームに移行する 7 つの理由無料トライアルマイグレーション（移行）は頭痛の種になることはありません。お問い合わせをお待ちしております。Databricks 無料トライアルDatabricks へのお問い合わせ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ 採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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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.プライバシー通知|利用規約|プライバシー設定|カリフォルニア州のプライバシー権利
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https://www.databricks.com/dataaisummit/speaker/anindya-saha
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Anindya Saha - 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 ExperiencePricingAnindya SahaML Platform Software Engineer at nullBack to speakersAnindya Saha is a Machine Learning Platform Engineer, focusing on enabling distributed computing solutions for machine learning and data engineering. He has led implementation of Spark on Kubernetes support on ml platform for feature engineering at scale. He also worked on enabling multi gpus multi nodes distributed model training on machine learning 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/artem-meshcheryakov/#
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Artem Meshcheryakov - 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 ExperiencePricingArtem MeshcheryakovConsultant at ORAYLIS GmbHBack to speakersArtem Meshcheryakov has been working in BI & BigData for more than 5 years.
Starting with Microsoft SQL Server and Oracle for traditional Data Warehousing Projects,
within several years he switched to modern data platforms in the Azure Cloud with the main focus on Azure Databricks.
For several years now, he has been working in this area,
he has been involved in building solutions using Azure Databricks at
large Scale and developing BigData Use Cases with Databricks.
At Oraylis, Artem works as a consultant and is responsible for implementing
large-scale modern data platform in various Azure cloud scenarios.
Artem is also a certified Databricks champion.
He is particularly interested in developing large-scale Big Data use cases
using Databricks and the Unity catalog in large enterprise environments.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/university-recruiting
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Databricks University Recruiting | 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 NOWShape tomorrowStart your career at Databricks and help data teams solve the world’s toughest problemsExplore opportunities OverviewCultureBenefitsDiversityStudents & new gradsStudent internships and college grad opportunitiesWe’re committed to learning and development at every level, so it’s important to our teams that we recruit and develop our next generation of Databricks leaders. Our University Program ensures that interns and new college grads play an integral role in developing our Platform, while participating in fun events to get to know each other and the larger Databricks team.Develop with an innovative global teamFounded in 2013 by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks has grown from a tiny corner office in Berkeley, California, to a company with employees all over the world.
Databricks has since become the industry leader for data-driven decision-making with its cloud-based infrastructure, collaborative workspace, team-based version control, integrated libraries for data manipulation and visualization, Spark-compatible optimized runtime environment, and robust security.WayUp Top 100 Internship Programs List for 2020Databricks is proud to be recognized on WayUp's Top 100 Internship Program.Read moreLife at DatabricksResources for studentsHear from the internsRead what it’s likeMastering engineering interviewsLearn the best tips & tricksUse Databricks in your classroomGet hands-on experienceCommunity edition of DatabricksTry out DatabricksFeeling good about our internship opportunities?See internship positionsSee all jobsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. 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/blog/2018/11/27/databricks-shows-off-aws-competencies-at-aws-reinvent.html#govcloud
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Databricks Shows off AWS Competencies at AWS re:Invent - 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 SectorDatabricks Shows off AWS Competencies at AWS re:Inventby Michael OrtegaNovember 27, 2018 in Company BlogShare this postPowering innovation on AWS in life sciences, public sector, machine learning, and big data analytics.Databricks, founded by the original creators of Apache SparkTM, is proud to be a Platinum sponsor at AWS re:Invent. Stop by booth #416 to grab some cool schwag and see demos of MLflow, TensorFlow, Apache Spark, and other technologies that are accelerating innovation at a growing number of companies, including HP, Shell, and NBCUniversal.
The AWS Competency Program is designed to highlight Amazon Partners that have demonstrated technical proficiency and customer success in specialized solution areas.
Here’s a quick overview of Databricks’ AWS Competencies:Databricks was recently recognized as an AWS Life Sciences Competency Partner, highlighting our success building innovative data analytics and machine learning solutions for Life Sciences organizations. Our Life Sciences solutions expand on the core capabilities of our Unified Analytics Platform with industry-specific toolsets to serve use cases across the drug development and precision medicine lifecycles.
Our first offering, the Databricks Unified Analytics Platform for Genomics, is designed to provide the scale and speed bioinformatics teams need to accelerate drug discovery and deliver precision care. Fully-managed in the AWS cloud, the platform provides collaborative workspaces for cross-disciplinary biomedical and pharmaceutical teams – from bioinformaticians to computational biologists to physician-scientists – to easily access, analyze, and extract novel insights from large volumes of genomic, imaging, and clinical datasets. The solution provides prebuilt best practice genomic pipelines and popular tertiary analytics tools in a secure, HIPAA compliant environment.
Customers including Regeneron, Sanford Health and the Human Longevity Institute have adopted Databricks to drastically scale and improve performance of their genomics workflows on AWS. Learn more about their use cases at our booth #416 at re:Invent.
The Databricks Unified Analytics Platform makes it easy for data science and engineering teams to collaborate with business teams around big data analytics and AI. We're focused on removing the challenges associated with AI adoption so that more businesses can fully harness its benefits.
Our AWS Machine Learning Competency highlights our expertise in artificial intelligence (AI) and machine learning. With the Databricks Unified Analytics Platform, data scientists and machine learning practitioners are empowered to analyze data at scale, train and deploy models with ease, and build powerful predictive applications.
A growing number of customers including Riot Games and Viacom have already delivered on innovative AI use cases with Databricks and AWS. Stop by booth #416 at re:Invent for a demo.
Data and analytics has become a strong competitive differentiator for most organizations. As an AWS Data & Analytics Competency Partner, Databricks has demonstrated success helping AWS customers improve the productivity of their data teams and draw insights from their data.
Transforming data into usable information can involve multiple tools and technologies. The Databricks Unified Analytics platform removes these obstacles, making it easy for organizations to turn data into value, from ingest through production, without the hassle of managing complex infrastructure, systems and tools. Visit our our booth #416 at re:Invent to learn more.
From providing better social services to preventing national threats, government agencies rely on secure, efficient and large-scale data processing and analysis to carry out their duties.
The Databricks Unified Analytics platform, recognized for it’s robust security model, has been available on the AWS GovCloud, an isolated AWS region designed to host sensitive and regulated data in the cloud, since 2016 and has the Authority to Operate in the AWS Commercial Cloud Service (C2S) for highly sensitive workflows. Databricks on AWS empowers government agencies to securely build and deploy advanced analytics solutions to meet a broad range of public sector use cases.
Visit our booth #416 at re:Invent to learn how we help government agencies simplify, scale and accelerate data analytics and AI for mission critical applications.
Make sure to check out reinvent to catch up on our latest announcements, demos and sessions taking place at re:Invent. If you're not able to visit us at re:Invent, stop by databricks.com/product/aws for our latest case studies, ebooks and customer webinars.Try Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. 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/fr/company/partners/consulting-and-si/partner-solutions?itm_data=menu-item-brickbuildersoverview
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Solutions partenaires - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT
Au revoir, entrepôt de données. Bonjour, Lakehouse.
Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne.
Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT
Découvrez le Lakehouse pour la fabrication
Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023
Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWSolutions partenairesDes solutions spécialisées pour le lakehouse et des outils de migration développés par nos partenairesNous sommes partenaires d'entreprises de premier plan spécialisées dans le conseil, afin de concevoir des solutions et des outils de migration innovants pour des cas d'usage spécifiques à votre secteur d'activité. Les Solutions Brickbuilder de Databricks sont conçues par nos partenaires pour vous aider à réduire les coûts et augmenter la valeur de vos données. Grâce à leurs années d'expérience dans le secteur et à leur forte implication dans la plateforme Databricks Lakehouse, vous avez la garantie de bénéficier de solutions adaptées à votre entreprise.Rechercher des partenaires disponiblessearchSecteur publicCloud Data Migration by Accenture - DatabricksEn savoir plusVente au détail et biens de consommationUnified View of Demand by AccentureEn savoir plusTechnologie marketing et publicitéCPG Control Tower by AvanadeEn savoir plusTechnologie marketing et publicitéIntelligent Healthcare on Azure Databricks by AvanadeEn savoir plusTechnologie marketing et publicitéIntelligent ManufacturingEn savoir plusTechnologie marketing et publicitéLegacy System Migration by AvanadeEn savoir plusTechnologie marketing et publicitéRisk Management by AvanadeEn savoir plusTechnologie et solutionsMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksEn savoir plusTechnologie et solutionsMigrate to Cloud and Databricks by Capgemini and DatabricksEn savoir plusTechnologie et solutionsCapgemini Revenue Growth ManagementEn savoir plusTechnologie et solutionsMigrate to Databricks by Celebal Technologies and DatabricksEn savoir plusTechnologie et solutionsCognizant Video Quality of ExperienceEn savoir plusTechnologie marketing et publicitéPersona 360 by DataSentics and DatabricksEn savoir plusTechnologie marketing et publicitéSAP Migration Accelerator by DataSentics - DatabricksEn savoir plusTechnologie marketing et publicitéPrecisionView™ by DeloitteEn savoir plusTechnologie marketing et publicitéTrellis by DeloitteEn savoir plusTechnologie marketing et publicitéSmart Migration to Databricks by EPAMEn savoir plusTechnologie marketing et publicitéLeapLogic Migration Solution by ImpetusEn savoir plusLIRE PLUSPrêt à vous lancer ?ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterD écouvrez les offres d'emploi
chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité|Conditions d'utilisation|Vos choix de confidentialité|Vos droits de confidentialité en Californie
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Realizing the Value of Real-World Evidence - DatabricksWhitepaperRemove the barriers to real-world evidence successEveryone knows real-world evidence (RWE) has value. But due to technology challenges, biopharma companies are struggling to achieve the full benefit of their RWE programs. Databricks recently surveyed 109 executives to get a better idea of what’s working, what’s not and the path forward.Get the full results in this whitepaper. You’ll find out:What benefits are driving investments in RWE programsWhich new types of real-world data will emerge in the next two yearsThe top factors inhibiting and contributing to RWE program successHow to build the ideal data architecture to unlock business outcomes with RWERead the whitepaperProductPlatform 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/vinod-marur
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Vinod Marur - 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 ExperiencePricingVinod MarurSVP of Engineering 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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Kontakt – DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT
Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse.
Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.
Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT
Entdecken Sie das Lakehouse für die Fertigung
Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023
Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWKontaktBrauchen Sie Hilfe bei Fortbildung oder Support? Dann rufen Sie diese zusätzlichen Ressourcen auf.DokumentationLesen Sie unsere technische Dokumentation zu Databricks auf AWS, Azure oder Google Cloud.Databricks-CommunityHier können Sie mit Databricks-Benutzern und Experten diskutieren, sich austauschen und sich vernetzen.WeiterbildungMeistern Sie die Databricks Lakehouse-Plattform mit Schulungen unter Anleitung und im Selbststudium oder werden Sie zertifizierter Entwickler.SupportSie sind schon Kunde? Dann klicken Sie hier, falls Sie ein technisches oder ein Zahlungsproblem haben.Unsere NiederlassungenZeigen Sie alle Niederlassungen weltweit an und nehmen Sie Kontakt auf.Knowledge BaseHier finden Sie schnelle Antworten auf die meistgestellten Fragen zu Databricks-Produkten und -Services.ProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter
„Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte
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Partnerlösungen – DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT
Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse.
Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt.
Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT
Entdecken Sie das Lakehouse für die Fertigung
Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023
Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLösungen von PartnernVon Partnern entwickelte Branchen- und Migrationslösungen für das LakehouseWir haben uns mit führenden Consulting-Partnern zusammengetan, um innovative Lösungen für branchen- und migrationsspezifische Anwendungsfälle zu entwickeln. Von unseren Partnern fachgerecht konzipiert, sollen Databricks Brickbuilder-Lösungen Sie dabei unterstützen, Kosten zu senken und den Mehrwert Ihrer Daten zu steigern. Dank der langjährigen Branchenerfahrung unserer Partner und der auf die Lakehouse-Plattform von Databricks zugeschnittenen Entwicklung können Sie auf Lösungen vertrauen, die für Ihr Unternehmen maßgeschneidert sind.Nach vorhandenen Partnern suchensearchÖffentlicher SektorCloud Data Migration by Accenture - DatabricksMehr InformationenEinzelhandel und KonsumgüterUnified View of Demand by AccentureMehr InformationenWerbe- und MarketingtechnologieCPG Control Tower by AvanadeMehr InformationenWerbe- und MarketingtechnologieIntelligent Healthcare on Azure Databricks by AvanadeMehr InformationenWerbe- und MarketingtechnologieIntelligent ManufacturingMehr InformationenWerbe- und MarketingtechnologieLegacy System Migration by AvanadeMehr InformationenWerbe- und MarketingtechnologieRisk Management by AvanadeMehr InformationenTechnologie und SoftwareMigrate Legacy Cards and Core Banking Portfolios by Capgemini and DatabricksMehr InformationenTechnologie und SoftwareMigrate to Cloud and Databricks by Capgemini and DatabricksMehr InformationenTechnologie und SoftwareCapgemini Revenue Growth ManagementMehr InformationenTechnologie und SoftwareMigrate to Databricks by Celebal Technologies and DatabricksMehr InformationenTechnologie und SoftwareCognizant Video Quality of ExperienceMehr InformationenWerbe- und MarketingtechnologiePersona 360 by DataSentics and DatabricksMehr InformationenWerbe- und MarketingtechnologieSAP Migration Accelerator by DataSentics - DatabricksMehr InformationenWerbe- und MarketingtechnologiePrecisionView™ by DeloitteMehr InformationenWerbe- und MarketingtechnologieTrellis by DeloitteMehr InformationenWerbe- und MarketingtechnologieSmart Migration to Databricks by EPAMMehr InformationenWerbe- und MarketingtechnologieLeapLogic Migration Solution by ImpetusMehr InformationenMEHR LADENMöchten Sie loslegen?DATABRICKS KOSTENLOS TESTENProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter
„Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
160 Spear Street, 13th Floor
San Francisco, CA 94105
1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte
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https://www.databricks.com/it/legal/privacynotice#dbadditionalinformation
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Master Cloud Services Agreement | 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 UpdatesMaster Cloud Services AgreementThis Master Cloud Services Agreement (the “MCSA”) is entered into as of the Effective Date between Databricks, Inc. (“Databricks” or “we”) and Customer (as defined below) and governs Customer’s use of the Databricks Services, including the right to access and use the Databricks data processing platform services (the “Platform Services”), on each cloud service where Databricks directly provides customers with access to such Platform Services. For the avoidance of doubt, this Agreement does not govern the use of Databricks Powered Services. Unless otherwise indicated, capitalized terms have the meaning assigned to them in this MCSA or in an incorporated Schedule.If you are entering into this MCSA on behalf of a company (such as your employer) or other legal entity, you represent and warrant that You are authorized to bind that entity to this MCSA, in which case “Customer,” “you,” or “your” will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind Your entity or do not agree with any provision of this MCSA, you must not accept this MCSA and may not use the Databricks Services.By accepting this MCSA, either by executing this MCSA, an Order, or another agreement that explicitly incorporates this MCSA by reference, Customer enters into the MCSA and the following Schedules, each of which are incorporated into the MCSA and apply to the provision of the applicable Databricks Services upon your ordering such service:Advisory ServicesTraining ServicesU.S. Public Sector ServicesYour Order may include one or more of the following: (a) the Platform Services, (b) support services (“Support Services“), (c) training services (“Training Services“), or (d) advisory services (“Advisory Services,” and together with any other services provided by Databricks, (a), (b), (c), and (d) shall be defined as the “Databricks Services”). You acknowledge that no term in any Order entered into via a reseller will be deemed to modify the Agreement unless pre-authorized in writing by Databricks. Definitions. Defined terms are set out below. Capitalized terms used but not defined in a Schedule or an Order will have the meaning assigned to them, if any, within this MCSA.
“Acceptable Use Policy” means the acceptable use policy governing the Platform Services located at databricks.com/legal/aup.“Affiliate” of a party means an entity that controls, is actually or in effect controlled by, or is under common control with such party.“Agreement” means this MCSA, the referenced Schedules, and any accompanying or future Order you enter into under this MCSA.“Authorized User” means employees or agents of Customer or its Affiliates selected by Customer to access and use the Platform Services.“Beta Service” means any feature of the Databricks Services ( that is clearly designated as “beta”, “experimental”, “preview” or similar, that is provided prior to general commercial release, and that Databricks at its sole discretion offers to Customer, and Customer at its sole discretion elects to use."Cloud Environment” means a cloud or other compute or storage infrastructure controlled by a party or by an external user (as may be defined where appropriate by schedule or amendment hereto) according to context and utilized under the Agreement.“Cloud Service Provider” means a cloud service provider on whose platform Databricks directly provides the Platform Services. For clarity, the Databricks Powered Services are not directly provided by Databricks and are not considered Platform Services under this Agreement.“Customer Content” means all data input into or made available by Customer for processing within the Platform Services or Support Services or generated from the Platform or Support Services.“Customer Data” means the data, other than Customer Instructional Input, made available by Customer and its Authorized Users for processing within the Platform Services or Support Services. “Customer Instructional Input” means information other than Customer Data that Customer inputs into the Platform Services to direct how the Platform Services process Customer Data, including without limitation the code and any libraries (including third party libraries) Customer utilizes within the Platform Services.“Customer Results” means any output Customer or its Authorized Users generate from their use of the Platform Services."Databricks Global Code of Conduct” means the Databricks Global Code of Conduct located at databricks.com/global-code-of-conduct.“Databricks Powered Service” means any third-party software or service powered by Databricks, including those at https://www.databricks.com/legal/cloud-provider-directory, that is provided to you under contractual terms between you and a third-party. This Agreement does not amend any term of such contract; the Databricks Powered Services are not considered Databricks Services (and, for the avoidance of doubt, are not considered Platform Services) under the Agreement and Databricks shall have no liability to you relating to your use of the Databricks Powered Services.“Documentation” means the documentation related to the Platform Services located at databricks.com/documentation.“DPA” means the Data Processing Addendum located at databricks.com/legal/dpa.“Effective Date” means the earliest of: the effective date of the initial Order that references this MCSA, the date of last signature of the MCSA, or the date you first access or use any Databricks Services.“Fees” means all amounts payable for Databricks Services.“HIPAA” means the Health Insurance Portability and Accountability Act of 1996, as amended and supplemented from time to time.“Intellectual Property Rights” means all worldwide intellectual property rights available under applicable laws including without limitation rights with respect to patents, copyrights, moral rights, trademarks, trade secrets, know-how, and databases.“Order” means an order form (“Order Form”), online order (including the provisioning of any Databricks Services) or similar agreement for the provision of Databricks Services, entered into by the parties or any of their Affiliates, incorporated by reference into, and governed by, the Agreement. By entering into an Order Form hereunder, an Affiliate agrees to be bound by the terms of this Agreement as if it were an original party hereto.“PCI-DSS” means the Payment Card Industry Data Security Standard.“PHI” means health information regulated by HIPAA or by any similar privacy law governing the use of or access to health information.“Security Addendum” means the Platform Security Addendum located at databricks.com/legal/security-addendum.“Schedule” means any of the schedules referenced herein or otherwise set forth in an Order.“Shared Data” means (i) Customer Content that you electto share with third parties or (ii) data you elect to receive from third parties, under an applicable configuration of the Platform Services.“Support Policy” means the available Support Services plans located at databricks.com/support.“System” means any application, computing or storage device, or network.“Usage Data” means usage data and telemetry collected by Databricks relating to Customer's use of the Platform Services. Usage Data may contain queries entered by an Authorized User but not the results of those queries.“Workspace” means a Platform Services environment.Confidentiality.Confidential Information. “Confidential Information” means any business or technical information disclosed by either party to the other that is designated as confidential at the time of disclosure or that, under the circumstances, a person exercising reasonable business judgment would understand to be confidential or proprietary. Without limiting the foregoing, all non-public elements of the Databricks Services are Databricks’ Confidential Information, Customer Content is Customer’s Confidential Information, and the terms of the Agreement and any information that either party conveys to the other party concerning data security measures, incidents, or findings constitute Confidential Information of both parties. Confidential Information will not include information that the receiving party can demonstrate (a) is or becomes publicly known through no fault of the receiving party, (b) is, when it is supplied, already known to whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others, (c) is independently obtained by whoever it is disclosed to in circumstances in which they are not prevented from disclosing it to others or (d) was independently developed by the receiving party without use of or reference to the Confidential Information.Confidentiality. A receiving party will not use the disclosing party’s Confidential Information except as permitted under the Agreement or to enforce its rights under the Agreement and will not disclose such Confidential Information to any third party except to those of its employees and/or subcontractors who have a bona fide need to know such Confidential Information for the performance or enforcement of the Agreement; provided that each such employee and/or subcontractor is bound by a written agreement that contains use and disclosure restrictions consistent with the terms set forth in this Section 2.2. Each receiving party will protect the disclosing party’s Confidential Information from unauthorized use and disclosure using efforts equivalent to those that the receiving party ordinarily uses with respect to its own Confidential Information of similar nature and in no event using less than a reasonable standard of care; provided, however, that a party may disclose such Confidential Information as required by applicable laws, subject to the party required to make such disclosure giving reasonable notice to the other party to enable it to contest such order or requirement or limit the scope of such request. The provisions of this Section 2.2 will supersede any non-disclosure agreement by and between the parties (whether entered into before, on or after the Effective Date) that would purport to address the confidentiality and security of Customer Content and such agreement will have no further force or effect with respect to Customer Content.Equitable Relief. Each party acknowledges and agrees that the other party may be irreparably harmed in the event that such party breaches Section 2.2 (Confidentiality), and that monetary damages alone cannot fully compensate the non-breaching party for such harm. Accordingly, each party hereto hereby agrees that the non-breaching party will be entitled to seek injunctive relief to prevent or stop such breach, and to obtain specific enforcement thereof. Any such equitable remedies obtained will be in addition to, and not foreclose, any other remedies that may be available.Intellectual Property.
Ownership of the Databricks Services. Except for the limited licenses expressly set forth in the Agreement, Databricks retains all Intellectual Property Rights and all other proprietary rights related to the Databricks Services. You will not delete or alter the copyright, trademark, or other proprietary rights notices or markings appearing within the Databricks Services as delivered to you. You agree that the Databricks Services are provided on a non-exclusive basis and that no transfer of ownership of Intellectual Property Rights will occur. You further acknowledge and agree that portions of the Databricks Services, including but not limited to the source code and the specific design and structure of individual modules or programs, constitute or contain trade secrets and other Intellectual Property Rights of Databricks and its licensors.Ownership of Customer Content. As between you and Databricks, you retain all ownership or license rights in Customer Content.Usage Data. Notwithstanding anything to the contrary in the Agreement, Databricks may collect and use Usage Data to develop, improve, operate, and support its products and services. Databricks will not share any Usage Data that includes Customer Confidential Information except either (a) to the extent that such Usage Data is anonymized and aggregated such that it does not identify Customer or Customer Confidential Information; or (b) in accordance with Section 2 (Confidentiality) of this Agreement.Feedback. You are under no duty to provide any suggestions, enhancement requests, or other feedback regarding the Databricks Services (“Feedback”). If you choose to offer Feedback to Databricks, you hereby grant Databricks a perpetual, irrevocable, non-exclusive, worldwide, fully-paid, sub-licensable, assignable license to incorporate into the Databricks Services or otherwise use any Feedback Databricks receives from you solely to improve Databricks products and services, provided that such Feedback is used in a manner that is not attributable to you. You also irrevocably waive in favor of Databricks any moral rights which you may have in such Feedback pursuant to applicable copyright law. Databricks acknowledges that any Feedback is provided on an “as-is” basis with no warranties of any kind.Use of the Platform Services.
Access. Databricks will make the Platform Services available to Customer and its Authorized Users in accordance with the terms and conditions of this Agreement, the Documentation, and an applicable Order.Databricks Responsibilities. Services. Databricks is responsible for (a) the operation of the Databricks Cloud Environment; and (b) the Databricks software used to operate the computing resources. Security Measures. Databricks shall implement reasonable administrative, physical, and technical safeguards to protect the security of the Platform Services and the Customer Content as set forth in the Security Addendum (“Security Measures”); and shall, without limiting the foregoing, maintain certification to ISO/IEC 27001:2013 or equivalent/greater standards during the term of this Agreement. Additionally, while it is your responsibility to back up Customer Content, Databricks will, at your reasonable request, provide commercially reasonable assistance with recovery efforts. While Databricks may update the Security Measures, it shall not materially diminish the effectiveness of the Security Measures.Customer Responsibilities. General Responsibilities. You acknowledge and agree that you are responsible for:
ensuring that each Authorized User has their own credentials, protecting those credentials, and not permitting any sharing of credentials;securing any Customer Cloud Environment, and any Customer System;backing up Customer Content; configuring the Platform Services in an appropriate way taking into account the sensitivity of the Customer Content that you choose to process using the Platform Services, including Shared Data; using commercially reasonable efforts to ensure that your Authorized Users review the portions of Documentation relevant to your use of the Platform Services and any security information published by Databricks and referenced therein that is designed to assist you in securing Customer Content;risks associated with all use of the Platform Services by an Authorized User under an Authorized User’s account (including for the payment of Fees related to such use), whether such action was taken by an Authorized User or by another party, and whether or not such action was authorized by an Authorized User, provided that such action was not (1) taken by Databricks or by a party acting under the direction of Databricks, or (2) an action by a third party that Databricks should reasonably have prevented. Use Limits. You will not, and will not permit your Authorized Users to:
violate the Acceptable Use Policy or use the Platform Services other than in accordance with the Documentation;copy, modify, disassemble, decompile, reverse engineer, or attempt to view or discover the source code of the Platform Services, in whole or in part, or permit or authorize a third party to do so, except to the extent such activities are expressly permitted by the Agreement or by law notwithstanding this prohibition;sell, resell, license, sublicense, distribute, rent, lease, or otherwise provide access to the Platform Services to any third party except to the extent explicitly authorized in writing by Databricks;use the Platform Services to develop or offer a service made available to any third party that could reasonably be seen to serve as a substitute for such third party’s possible purchase of any Databricks product or service;transfer or assign any of your rights hereunder except as permitted under Section 12.5 (Assignment); orduring any free trial period granted by Databricks, including during the use of any Beta Service, use the Databricks Services for any purpose other than to evaluate whether to purchase the Databricks Services.Shared Responsibilities. Customer acknowledges that the Platform Services may be implemented in a manner that divides the Platform Services between the Customer Cloud Environment and the Databricks Cloud Environment, and that accordingly each party must undertake certain technical and organizational measures in order to protect the Platform Services and the Customer Content. Permitted Benchmarking. You may perform benchmarks or comparative tests or evaluations (each, a “Benchmark”) of the Platform Services and may disclose the results of the Benchmark other than for Beta Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Platform Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii) agree that we may perform and disclose the results of Benchmarks of your products or services, irrespective of any restrictions on Benchmarks in the terms governing your products or services.Customer Content.Limits on What Customer Content May Contain. You agree that you will not include in Customer Content, or generate any Customer Results that include, any data for which you do not have all rights, power and authority necessary for its collection, use and processing as contemplated by the Agreement.PHI Data. You shall not include in Customer Content any PHI unless (a) you have entered into an Order permitting you to process PHI, and then only with respect to the Workspace(s) or account (if applicable) (together the “PHI Permitted Workspaces”) identified on such Order; and (b) you have entered into a Business Associate Agreement (“BAA”) with Databricks. If you have not entered into a BAA with Databricks or if you provide PHI to Databricks other than through the PHI Permitted Workspaces, Databricks will have no liability under the Agreement relating to PHI notwithstanding anything in the Agreement or in HIPAA or any similar laws to the contrary.Cardholder Data. You shall not include in Customer Content any cardholder data as defined under PCI-DSS (“Cardholder Data”) unless (1) you are processing the Cardholder Data in a PCI Permitted Workspace and configure and operate such Workspace in accordance with the Documentation; and (2) you have entered into an Order that (a) specifies Databricks then-current certification status under PCI-DSS; and (b) explicitly permits you to process Cardholder Data within the Platform Services (including specifying the types and quantities of such data) and then only with respect to the Workspace(s) identified in such Order (the “PCI Permitted Workspaces”). Databricks will have no liability under the Agreement relating to Cardholder Data that is not processed in accordance with the terms of this section notwithstanding anything in the Agreement or in PCI-DSS or any similar regulations to the contrary.Architectures and Services Updates. Databricks provides the Platform Services according to different architectural models (e.g. models where computing resources are deployed into Customer Cloud Environment and models where computing resources are deployed into Databricks Cloud Environments) depending on the specific feature being used by Customer, as further described in the Documentation. Accordingly, Customer acknowledges and agrees that different portions of the Platform Services are and may in the future be subject to changes reflected in the Documentation or terms and conditions that provide for different rights and responsibilities of the parties for their use. Databricks Container ServicesAs part of Databricks Container Services, Databricks may provide a sample stub container file (a “Sample Container”) that you may use to create a custom container file (a “Modified Sample Container”). Databricks grants you a limited, non-exclusive right and license to use and modify the Sample Container to create a Modified Sample Container to use with Databricks Container Services. The Sample Container may contain libraries that are subject to open source licenses. It is your obligation to review and comply with any such licenses prior to your creation of the Modified Sample Container.You may not:
include in a Custom Container any code: (i) for which you do not have the necessary right or license; or (ii) that contains any code that could subject Databricks to any condition that Databricks make any of its source code available or which may impose any other obligation or restriction with respect to Databricks’ Intellectual Property Rights; orattempt to disable or interfere with any technical limitations contained within Databricks Container Services.You grant Databricks a worldwide, non-exclusive royalty free right and license to use, reproduce and make derivative works of the Custom Container solely as necessary to provide Databricks Container Services to Customer.Data Protection. Except with respect to a free trial, the terms of the DPA are hereby incorporated by reference and shall apply to the processing of personal data as described in the DPA.Suspension and Termination of Platform Services.
Suspension. Databricks may temporarily suspend any or all Workspaces at any time: (i) immediately without notice if Databricks reasonably suspects that you have violated your obligations under Section 4.3 (Customer Responsibilities), Section 4.6 (Customer Content), or Section 11 (Compliance with Laws) in a manner that may cause material harm or material risk of harm to Databricks or to any other party; (ii) or if you (or any third party responsible for making payment on your behalf) fail to pay undisputed Fees after receiving notice that you are delinquent in payment.Termination; Workspace Cancellation. Databricks may terminate your use of the Platform Services and any Workspaces and any applicable Order for material breach, including without limitation your breach of Section 4.10(a), that in each case is either not cured within thirty (30) days of notice of such breach or that by its nature is incapable of cure. If the Agreement or any applicable Order is terminated for any reason or upon your written request, Databricks may cancel your Workspaces. Upon termination of the Agreement for any reason you will delete all stored elements of the Platform Services from your Systems.Deletion of Customer Content upon Workspace Cancellation. Databricks will automatically delete all Customer Content contained within a Workspace within thirty (30) days following the cancellation of such Workspace. Monthly Pay-As-You-Go (PAYG) Services. Notwithstanding anything in the Agreement to the contrary, Databricks may suspend or terminate any Platform Services provided on a month-to-month basis with payment based only on Customer’s usage of the Platform Services during the billing month and delete any Customer Content relating to such Workspace that may be stored within the Platform Services or other Databricks’ Systems, upon thirty (30) days’ prior written notice (email sufficient) if Databricks reasonably determines the account is inactive as set forth in the Acceptable Use Policy.Notice. Notwithstanding Section 12.6 (Notice), notice under this Section 4.10 (Suspension; Termination) may be provided by email sent to a person the party providing notice reasonably believes to have responsibility for the other party’s activities under the Agreement.Support Services. Databricks will provide you with the level of Support Services specified in an Order in accordance with the Support Policy. If Support Services are not specified in an Order, your support shall be limited to public Documentation and forums.Warranties; Remedy.Warranties. Each party warrants that it is validly entering into the Agreement and has the legal authority to do so. In addition to the warranties provided by the parties as set forth in any applicable Schedule, Databricks warrants that, during the term of any Order for Platform Services: (a) the Platform Services will function substantially in accordance with the Documentation; and (b) Databricks will employ commercially reasonable efforts in accordance with industry standards to prevent the transmission of malware or malicious code via the Platform Services.Disclaimer. THE WARRANTIES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES) ARE EXCLUSIVE AND IN LIEU OF ALL OTHER WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, REGARDING DATABRICKS AND DATABRICKS’ SERVICES PROVIDED HEREUNDER. DATABRICKS AND ITS LICENSORS SPECIFICALLY DISCLAIM ALL IMPLIED WARRANTIES, CONDITIONS AND OTHER TERMS, INCLUDING, WITHOUT LIMITATION, IMPLIED WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY OR FITNESS FOR A PARTICULAR PURPOSE. NOTWITHSTANDING ANYTHING TO THE CONTRARY HEREIN: (a) ANY SERVICES PROVIDED UNDER ANY FREE TRIAL PERIOD ARE PROVIDED “AS-IS” AND WITHOUT WARRANTY OF ANY KIND; (b) WITHOUT LIMITATION, DATABRICKS DOES NOT MAKE ANY WARRANTY OF ACCURACY, COMPLETENESS, TIMELINESS, OR UNINTERRUPTABILITY, OF THE PLATFORM SERVICES; (c), DATABRICKS IS NOT RESPONSIBLE FOR RESULTS OBTAINED FROM THE USE OF THE DATABRICKS SERVICES OR FOR CONCLUSIONS DRAWN FROM SUCH USE; AND (d) EXCEPT AS OTHERWISE STATED IN SECTION 4 (USE OF THE PLATFORM SERVICES), DATABRICKS’ REASONABLE EFFORTS TO RESTORE LOST OR CORRUPTED CUSTOMER INSTRUCTIONAL INPUT DESCRIBED THEREIN SHALL BE DATABRICKS’ SOLE LIABILITY AND YOUR SOLE AND EXCLUSIVE REMEDY IN THE EVENT OF ANY LOSS OR CORRUPTION OF CUSTOMER CONTENT IN CONNECTION WITH THE DATABRICKS SERVICES.Platform Services Warranty Remedy. FOR ANY BREACH OF THE WARRANTIES RELATED TO THE PLATFORM SERVICES PROVIDED BY DATABRICKS IN SECTION 6.1 (WARRANTIES), YOUR EXCLUSIVE REMEDY AND DATABRICKS’ ENTIRE LIABILITY WILL BE THE MATERIAL CORRECTION OF THE DEFICIENT SERVICES THAT CAUSED THE BREACH OF WARRANTY, OR, IF WE CANNOT SUBSTANTIALLY CORRECT THE DEFICIENCY IN A COMMERCIALLY REASONABLE MANNER, DATABRICKS WILL END THE DEFICIENT SERVICES AND REFUND TO YOU THE PORTION OF ANY PREPAID FEES PAID BY YOU TO DATABRICKS APPLICABLE TO THE PERIOD FOLLOWING THE EFFECTIVE DATE OF TERMINATION.Indemnification.
Indemnification by Databricks. Subject to Section 7.5 (Conditions of Indemnification), Databricks will defend Customer against any claim, demand, suit or proceeding made or brought against Customer by a third party (a “Claim Against Customer”)alleging that the Databricks Services as provided to Customer by Databricks or Customer’s use of the Databricks Services in accordance with the Documentation and the Agreement infringes or misappropriates such party’s Intellectual Property Rights (an “IP Claim”), and will indemnify Customer from and against any damages, attorney fees and costs finally awarded against Customer as a result of, or for amounts paid by Customer under a settlement approved by Databricks in writing of, a Claim Against Customer. Notwithstanding the foregoing, Databricks will have no liability for any infringement or misappropriation claim of any kind if such claim arises from: (a) the public open source version of Apache Spark (located at github.com/apache/spark) if the claim of infringement or misappropriation does not allege specifically that the infringement or misappropriation arises from the Platform Services (as opposed to Apache Spark itself); (b) the combination, operation or use of the Databricks Services with equipment, devices, software or data (including without limitation your Confidential Information) not supplied by Databricks if a claim would not have occurred but for such combination, operation or use; or (c) your or an Authorized User’s use of the Databricks Services other than in accordance with the Documentation and the Agreement.Other Remedies. If Databricks receives information about an infringement or misappropriation claim related to a Databricks Service or otherwise becomes aware of a claim that the provision of any of the Databricks Services is unlawful in a particular territory, then Databricks may at its sole option and expense: (a) replace or modify the applicable Databricks Services to make them non-infringing and of substantially equivalent functionality; (b) procure for you the right to continue using the Databricks Services under the terms of the Agreement; or (c) if Databricks is unable to accomplish either (a) or (b) despite using its reasonable efforts, terminate your rights and Databricks’ obligations under the Agreement with respect to such Databricks Services and refund to you any Fees prepaid by you to Databricks for Databricks Services not yet provided.Indemnification by Customer. Subject to Section 7.5 (Conditions of Indemnification), Customer will defend Databricks against any claim, demand, suit or proceeding made or brought against Databricks by a third party (a “Claim Against Databricks”) (a) arising from or related to Customer’s use of the Databricks Services in violation of any applicable laws, the rights of a third party, or the Agreement, or (b) arising from or related to Customer Content or its use with the Databricks Services, (c) alleging that any information and / or materials you provide to Databricks for Databricks to perform Advisory Services as defined in an Advisory Services Schedule (if applicable) (“Customer Materials”) or the use of Customer Materials with the Databricks Services infringes or misappropriates such party’s Intellectual Property Rights, and / or (d) arising from any instructions provided by Customer to Databricks in the creation by Databricks of the Deliverables (as defined in the Advisory Services Schedule (if applicable)), and will indemnify Databricks from and against any damages, attorney fees and costs finally awarded against Databricks as a result of a Claim Against Databricks, or for amounts paid by Databricks under a settlement approved by Customer in writing.Sole Remedy. SUBJECT TO SECTION 7.5 (CONDITIONS OF INDEMNIFICATION) BELOW, THE FOREGOING SECTIONS 7.1 (INDEMNIFICATION BY DATABRICKS) AND 7.2 (OTHER REMEDIES) STATE THE ENTIRE OBLIGATION OF DATABRICKS AND ITS LICENSORS WITH RESPECT TO ANY ALLEGED OR ACTUAL INFRINGEMENT OR MISAPPROPRIATION OF INTELLECTUAL PROPERTY RIGHTS BY THE DATABRICKS SERVICES.Conditions of Indemnification. As a condition to an indemnifying party’s (each, an “Indemnitor”) obligations under this Section 7 (Indemnification), a party seeking indemnification (each, an ”Indemnitee”) will: (a) promptly notify the Indemnitor of the claim for which the Indemnitee is seeking indemnification (but late notice will only relieve Indemnitor of its obligation to indemnify to the extent that it has been prejudiced by the delay); (b) grant the Indemnitor sole control of the defense (including selection of counsel) and settlement of the claim; (c) provide the Indemnitor, at the Indemnitor’s expense, with all assistance, information and authority reasonably required for the defense and settlement of the claim; and (d) preserve and will not waive legal, professional or any other privilege attaching to any of the records, documents, or other information in relation to such claim without prior notification of consent by the Indemnitor. The Indemnitor will not settle any claim in a manner that does not fully discharge the claim against an Indemnitee or that imposes any obligation on, or restricts any right of, an Indemnitee without the Indemnitee’s prior written consent, which may not be unreasonably withheld or delayed. An Indemnitee has the right to retain counsel, at the Indemnitee’s expense, to participate in the defense or settlement of any claim. The Indemnitor will not be liable for any settlement or compromise that an Indemnitee enters into without the Indemnitor’s prior written consent.Limitation of Liability.
EXCEPT WITH RESPECT TO (I) LIABILITY THAT CANNOT BE EXCLUDED OR LIMITED BY APPLICABLE LAWS, (II) LIABILITY ARISING OUT OF FRAUD OR FRAUDULENT MISREPRESENTATION, OR (III) CUSTOMER’S INDEMNIFICATION OBLIGATIONS, NEITHER PARTY WILL HAVE ANY LIABILITY FOR: (A) INDIRECT, INCIDENTAL, SPECIAL, PUNITIVE, OR CONSEQUENTIAL LOSS OR DAMAGES; (B) LOST PROFITS OR REVENUE; (C) LOSS OF GOODWILL; (D) LOSS OF DATA; OR (E) LOSS ARISING FROM INACCURATE OR UNEXPECTED RESULTS ARISING FROM THE USE OF THE DATABRICKS SERVICES, REGARDLESS OF WHETHER SUCH PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES OR DAMAGES ARISING.SUBJECT TO SECTIONS 8.1, 8.3, 8.4 AND 8.5, EXCEPT WITH RESPECT TO LIABILITY ARISING OUT OF: (I) PERSONAL INJURY OR DEATH CAUSED BY THE NEGLIGENCE OF A PARTY, ITS EMPLOYEES, OR AGENTS; (II) DATABRICKS’ INDEMNIFICATION OBLIGATIONS FOR AN IP CLAIM; OR (III) CUSTOMER’S INDEMNIFICATION OBLIGATIONS, IN NO EVENT WILL THE AGGREGATE LIABILITY OF EACH PARTY TOGETHER WITH ALL OF ITS AFFILIATES ARISING OUT OF OR RELATED TO THE AGREEMENT EXCEED THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (THE “GENERAL CAP”). THE FOREGOING LIMITATION WILL APPLY WHETHER AN ACTION IS IN CONTRACT OR TORT AND REGARDLESS OF THE THEORY OF LIABILITY, BUT WILL NOT LIMIT CUSTOMER’S AND ITS AFFILIATES’ PAYMENT OBLIGATIONS UNDER SECTION 10 (PAYMENT).SUBJECT TO SECTIONS 8.1, 8.4 AND 8.5, DATABRICKS’ AGGREGATE LIABILITY FOR ANY CLAIMS OR DAMAGES, DIRECT OR OTHERWISE, ARISING OUT OF OR IN CONNECTION WITH DATABRICKS’ BREACH OF ITS CONFIDENTIALITY OBLIGATIONS (SECTION 2.2) OR, WITH RESPECT TO THE PROVISION BY DATABRICKS OF THE PLATFORM SERVICES (IF APPLICABLE), THE DATA PROTECTION AND SECURITY OBLIGATIONS SET FORTH IN THIS AGREEMENT AND THE DPA, WHERE SUCH BREACH RESULTS IN UNAUTHORIZED DISCLOSURE OF CUSTOMER CONTENT, EXCEPT TO THE EXTENT SUCH CLAIMS OR DAMAGES ARE CAUSED BY DATABRICKS’ GROSS NEGLIGENCE OR WILLFUL MISCONDUCT, SHALL BE LIMITED TO TWO (2) TIMES THE TOTAL AMOUNT PAID BY CUSTOMER AND ITS AFFILIATES FOR THE DATABRICKS SERVICES GIVING RISE TO THE LIABILITY IN THE TWELVE (12) MONTHS PRECEDING THE FIRST INCIDENT OUT OF WHICH THE LIABILITY AROSE (“SUPERCAP”).IN NO EVENT SHALL DATABRICKS BE LIABLE FOR THE SAME EVENT UNDER BOTH THE GENERAL CAP AND THE SUPERCAP. SIMILARLY, THOSE CAPS SHALL NOT BE CUMULATIVE; IF THERE ARE ONE OR MORE CLAIMS SUBJECT TO EACH OF THOSE CAPS, THE MAXIMUM TOTAL LIABILITY FOR ALL CLAIMS IN THE AGGREGATE SHALL NOT EXCEED THE SUPERCAP.NOTWITHSTANDING ANYTHING CONTAINED ABOVE, DATABRICKS' LIABILITY RELATING TO BETA SERVICES OR ANY DATABRICKS SERVICES PROVIDED FREE OF CHARGE, INCLUDING ANY DATABRICKS SERVICES PROVIDED DURING A FREE TRIAL PERIOD, WILL BE LIMITED TO FIVE THOUSAND US DOLLARS (USD $5,000).TermTerm of Agreement. The Agreement will become effective on the Effective Date and will continue in full force and effect until terminated by either party pursuant to this Section 9 (Term). The Agreement may be terminated (i) by either party on thirty (30) days’ prior written notice if (a) there are no operative Orders outstanding or (b) the other party is in material breach of the Agreement and the breaching party fails to cure the breach prior to the end of the notice period; or (ii) by Databricks upon thirty (30) days’ prior written notice following your receipt of a notice that you are delinquent in the payment of undisputed Fees. If the Agreement terminates pursuant to the prior sentence due to Databricks’ material breach, Databricks will refund to you that portion of any prepayments made to Databricks related to Databricks Services not yet provided. Either party can immediately terminate the Agreement if the other becomes insolvent, makes an assignment for the benefit of its creditors, has a receiver, examiner, or administrator of its undertaking of the whole or a substantial part of its assets appointed, or an order is made, or an effective resolution is passed, for its administration, examinership, receivership, liquidation, winding-up or other similar process, or has any distress, execution or other process levied or enforced against the whole or a substantial part of its assets (which is not discharged, paid out, withdrawn or removed within 30 days), or is subject to any proceedings which are equivalent or substantially similar to any of the foregoing under any applicable jurisdiction, or ceases to conduct business or threatens to do so.Term of Orders. The Term of an Order will be as specified in the Order.Survival. All provisions of the Agreement that by their nature should survive termination will so survive.Payment. Unless your usage of the Databricks Services is being paid for by a third party under contract with Databricks, you will pay all Fees specified in the applicable Order. With respect to direct Order, except as otherwise specified therein: (a) all Fees owed to Databricks will be paid in U.S. Dollars; (b) invoiced payments will be due within 30 days of the date of your receipt of each invoice; (c) Fees for all prepaid committed Databricks Services will be invoiced in full upon execution of the applicable Order; and (d) all excess usage will be invoiced monthly in arrears. With respect to an Order entered into with a reseller, payment terms will be specified on such Order, provided that should you fail to pay Fees when due to a Databricks-authorized reseller, Databricks may seek payment directly from you. All past due payments, except to the extent reasonably disputed, will accrue interest at the highest rate allowed under applicable laws but in no event more than one and one-half percent (1.5%) per month. You will be solely responsible for payment of any applicable sales, value added or use taxes, or similar government fees or taxes.Compliance with Laws.By Databricks Generally. Databricks will provide the Databricks Services in accordance with its obligations under laws and government regulations applicable to Databricks’ provision of the Databricks Services to its customers generally, including, without limitation those related to data protection and data privacy, irrespective of Customer’s particular use of the services.By Customer Generally. You represent and warrant to Databricks that your use of Databricks Services will comply with all applicable laws and government regulations, including without limitation those related to data protection and data privacy. Export Controls; Trade Sanctions. The Databricks Services may be subject to export controls and trade sanctions laws of the United States and other jurisdictions. Customer acknowledges and agrees that it will comply with all applicable export controls and trade sanctions laws, regulations and/or any other relevant restrictions in Customer’s use of the Databricks Services, including that you will not permit access to or use of any Databricks Services in any country where such access or use is subject to a trade embargo or prohibition, and that you will not use Databricks Services in support of any controlled technology, industry, or goods or services, or any other restricted use, without having a valid governmental license, authority, or permission to engage in such conduct. Each party further represents that it (and with respect to Customer, each Authorized User and / or Affiliate accessing the Databricks Services) is not named on any governmental or quasi-governmental denied party or debarment list relevant to this Agreement, and is not owned directly or indirectly by persons whose aggregated interest in such party is 50% or more and who are named on any such list(s). Business Practices; Code of Conduct. Databricks maintains a set of business practice principles and policies in the Databricks Global Code of Conduct, which employees are required to follow. Databricks will abide by these principles and policies in the conduct of all business for Customer and expects your use of any Databricks Services to be conducted utilizing principles of business ethics and social responsibility and, with respect to any Platform Services, in accordance with Databricks’ Acceptable Use Policy and the applicable Platform Services terms set forth in the Agreement.General.
Governing Law and Venue. The governing law and exclusive venue applicable to any lawsuit or other dispute arising in connection with the Agreement will be determined by the location of Customer’s principal place of business (“Domicile”), as follows:
Customer’s DomicileGoverning LawVenue(courts with exclusive jurisdiction)CaliforniaCaliforniaSan Francisco(state and U.S. federal courts)Americas (except California and Canada); Middle East; AfricaDelawareDelaware(state and U.S. federal courts)CanadaOntarioTorontoUnited KingdomEngland & WalesLondonEurope (including Turkey)IrelandDublinPacific & AsiaSingaporeSingaporeAustralia and New ZealandAustraliaVictoriaThe parties hereby irrevocably consent to the personal jurisdiction and venue of the courts in the venues shown above. Unless prohibited by governing law or venue, each party irrevocably agrees to waive jury trial. In all cases, the application of law will be without regard to, or application of, conflict of law rules or principles, and the United Nations Convention on Contracts for the International Sale of Goods will not apply.Insurance Coverage.Databricks will maintain commercially appropriate insurance coverage given the nature of the Databricks Services and Databricks’ obligations under the Agreement. Such insurance will be in an industry standard form with licensed insurance carriers with A.M. Best ratings of A-IX or better, and will include commercially appropriate cyber liability insurance coverage. Upon request, Databricks will provide Customer with certificates of insurance evidencing such coverage.Entire Agreement, Construction, Amendment and Execution. The Agreement is the complete and exclusive understanding and agreement between the parties regarding its subject matter, provided that to the extent Customer uses any Databricks Services subject to Schedules not included in the Agreement, the relevant Schedule in effect at the time of first use at databricks.com/legal/mcsa shall be deemed to govern use of such Databricks Services unless the parties agree otherwise in writing and any reference to a term in such Schedule shall be interpreted accordingly. Databricks may change and update the Platform Services, in which case Databricks may update the Documentation. To the extent any provision in an Order clearly conflicts with a provision of this MCSA or a provision of an earlier Order, the provision in the new Order will be binding and the conflicting provision in this MCSA or in the earlier Order will be deemed modified solely to the extent reasonably necessary to eliminate the conflict and solely with respect to the new Order (unless expressly intended to permanently amend the Agreement including any Schedule). Customer’s Affiliates may receive the Databricks Services under this Agreement as Authorized Users, however in the event that a Customer Affiliate wishes to execute its own Order subject to the terms of this Agreement then Customer agrees to remain jointly and severally liable for such use. If any provision of the Agreement is held to be unenforceable or invalid, that provision will be enforced to the maximum extent possible and the other provisions will remain in full force and effect. The headings in the Agreement are solely for convenience and will not be taken into consideration in interpretation of the Agreement. Any translation of the Agreement or an Order that is provided as a courtesy shall not be legally binding and the English language version will always prevail. Each party acknowledges and agrees that it has adequate sophistication, including legal representation, fully to review and understand the Agreement; therefore, in interpretation of the Agreement with respect to any drafting ambiguities that may be identified or alleged, no presumption will be given in favor of the non-drafting party. The Agreement may not be modified or amended except by mutual written agreement of the parties. Without limiting the foregoing, no Customer purchase order will be deemed to modify an Order or the Agreement unless expressly pre-authorized in writing by Databricks. The Agreement may be executed in two or more counterparts, each of which will be deemed an original and all of which, taken together, will constitute one and the same instrument. A party’s electronic signature or transmission of any document by electronic means will be deemed to bind such party as if signed and transmitted in physical form.Publicity. Customer consents to Databricks’ use of Customer's name and logo for public identification as a customer, along with general descriptions of any non-confidential matters Databricks has handled for Customer in promotional marketing materials and press releases. In addition, upon request, Customer consents to participating in a case study regarding its experiences with the Databricks Services ("Case Study"), and inclusion of the Case Study in promotional marketing materials and press releases.Assignment. No assignment, novation or transfer of a party’s rights and obligations under the Agreement (“Assignment”) is permitted except with the prior written approval of the other party, which will not be unreasonably withheld. Notwithstanding the foregoing, either party may freely make an Assignment to a successor in interest upon a change of control; if such Assignment is to a direct competitor of the other party or would cause the other party to become in violation of applicable laws that is not reasonably addressable, such other party may terminate the Agreement upon written notice.Notice. Any required notice under the Agreement will be deemed given when received by letter delivered by nationally recognized overnight delivery service or recorded prepaid mail. Unless notified in writing of a change of address, you will send any required notice to Databricks, Inc., 160 Spear Street, Suite 1300, San Francisco, CA 94105, USA, attention: Legal Department, or to the alternative Databricks Affiliate (if any) identified in an applicable Order, and Databricks will send any required notice to you directed to the most recent address you have provided to Databricks for such notice.Force Majeure. Neither party will be liable or responsible to the other party nor be deemed to have defaulted under or breached the Agreement for any failure or delay in fulfilling or performing any term of the Agreement (except for any obligations to make payments to the other party), when and to the extent such failure or delay is caused by or results from acts beyond the impacted party’s (“Impacted Party”) reasonable control, including without limitation the following force majeure events (“Force Majeure Event(s)“): (a) acts of God, (b) acts of government, including any changes in law or regulations, (c) acts or omissions of third parties, (d) flood, fire, earthquakes, civil unrest, wars, acts of terror, pandemics, or strikes or other actions taken by labor organizations, (e) computer, telecommunications, the Internet, Internet service provider or hosting facility failures or delays involving hardware, software or power systems not within the Impacted Party’s possession or reasonable control, (f) network intrusions or denial of service attacks, or (g) any other cause, whether similar or dissimilar to any of the foregoing, that is beyond the Impacted Party’s reasonable control.Last Updated December 1, 2022. 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Yaniv Kunda - 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 ExperiencePricingYaniv KundaSenior Software Architect at AkamaiBack to speakersYaniv Kunda is a Senior Software Architect at Akamai. With more than 25 years of experience in software engineering and with a particular interest in the infrastructural aspects of the systems he worked on, Yaniv has been focusing on Big Data for the past 4 years. He holds a BA in Computer Sciences from the Interdisciplinary Center Herzliya.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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Jeff Breeding-Allison - 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 ExperiencePricingJeff Breeding-AllisonSenior Data Scientist at Mars PetcareBack to speakersJeff Breeding-Allison is a Senior Data Scientist at Mars Petcare with years of experience working in demand forecasting at CPG and marketing companies. He was previously a Visiting Assistant Professor of Mathematics at Boston College and at Fordham University in NYC, where he published research on modular forms, automorphic representations, and the representation theory of finite general symplectic groups.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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Yeshwanth Vijayakumar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYeshwanth VijayakumarSr Engineering Manager/Architect at AdobeBack to speakersYeshwanth Vijayakumar is a Sr Engineering Manager/Architect on the Unified Profile Team in the Adobe Experience Platform; it’s a PB scale store with a strong focus on millisecond latencies and analytical abilities and easily one of Adobe’s most challenging SaaS projects in terms of scale. He is actively designing/implementing the Interactive segmentation capabilities which helps us segment over two million records per second using Apache Spark. He looks for opportunities to build new features using interesting data Structures and Machine Learning approaches. In a previous life, he was a ML Engineer on the Yelp Ads team building models for Snippet Optimizations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
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製造業向けソリューション | DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT
さようなら、データウェアハウス。こんにちは、レイクハウス。
データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。
今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)
製造業のためのレイクハウスを発見する
コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日
直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOW製造業向けレイクハウスの活用製造業におけるデータ活用のために構築された唯一のデータプラットフォームで、コスト削減、生産性向上、データエコシステムの統合を実現ご登録ご相談・お問い合わせ低コスト、高性能、スケーラビリティ製造業のためのレイクハウスデータ、分析、AI のワークロードを全て統合して共有とガバナンスを組み込むことができれば、社内外のチームは必要なときに必要なデータにアクセスできるようになります。バリューチェーン全体への影響顧客エンゲージメント正確な成果と摩擦のない顧客体験顧客、運用、資産の 360 度ビューにより、製品のライフサイクルにわたって最高の稼働時間、サービス品質、経済価値を提供し、パーソナライズされた顧客成果やプロアクティブなフィールドサービスの提供、差別化されたミッションクリティカルなソリューションを強化します。運用効率の改善従業員の生産性向上製品イノベーション製造ソリューションとパートナー製造業に特化した妥協のないデータ分析・AI ソリューションDatabricks ソリューションアクセラレータは、成果創出を加速するフル機能の Notebook やベストプラクティスを含む目的に沿ったガイドです。ソリューションアクセラレータを使用することで、デジタルツイン、設備全体の効果、予測などのユースケースにおける発見、設計、開発、テストにかかる時間を短縮し、製造業の成果を加速させます。設備総合効率と KPI モニタリング性能と拡張性に優れたエンドツーエンドの設備監視を実現
センサー /IoT デバイスからのさまざまな形式のデータを段階的に取り込んで処理し、KPI やメトリクスを計算して表面化し、価値ある知見を導き出します。無料トライアル部品レベルの需給予測部品レベルでの需要予測による製造の効率化
需要予測を集計レベルではなく部品レベルで行うことで、サプライチェーンの混乱を最小化し、収益の拡大を図ります。無料トライアルデジタルツイン運用効率の向上と意思決定の改善
実世界のデータをリアルタイムで処理して知見を大規模に計算し、複数のダウンストリームアプリケーションに配信して、データドリブンな意思決定で工場設備の運用を最適化します。無料トライアル製造業向けアクセラレーターを見るDatabricks は、主要なコンサルティングパートナー との連携を通じて、各業界固有の革新的なソリューションを構築しています。深い専門知識と長年の経験を持つパートナーによる設計に基づく Databricks の Brickbuilder は、Databricks のレイクハウス向けに構築されており、コスト削減とデータ価値の最大化を可能にするソリューションです。お客さまのニーズに最適なソリューションが見つかります。インテリジェントな製造 データを活用して相互運用性を促進し、分析と AI を使用して知見を大規模に提供します。詳しく見るQuality Inspectorコンピュータビジョンにより欠陥、異物、異常、誤ったセットアップを検出し、品 質管理を自動化します。詳しく見る予測型サプライリスク管理注文の流れとサプライヤーのパフォーマンスを N 層で可視化することにより、効率性を高め、例外を管理し、回復力を向上させます。詳しく見る全てのパートナーソリューションを見る「Databricks のレイクハウスは、私たちが世界で最も革新的で信頼性の高い電気自動車を製造できるように、組織全体におけるデータアクセスの参入障壁を低くするためのちからを与えてくれます。」
Rivian 社 ソフトウェア開発担当 VP ワッシム・ベンサイド氏
「Databricks の応用範囲はここ数年で大きく拡大しました。導入当初はビッグデータと AI のプラットフォームとして使用していましたが、現在ではユースケースが広がり、それぞれ異なる目的を持った市民エンジニアやデータサイエンティストが最新の BI ツールとして利用しています。Databricks は、データドリブンな意思決定を支えています。」
シェル社 高度分析 CoE
ゼネラルマネージャー
ダニエル・ジーボンズ氏
「Databricks のプラットフォームは、エンジンの可用性に対するリスクの最小化、スペアパーツの調達リードタイムの短縮、在庫回転の効率化などに役立っています。これら全てが、航空業界をリードする PBH（Power-by-the-Hour）メンテナンスプログラムである TotalCare の提供を可能にしています。」
ロールス・ロイス シビルエアロスペース社 CIO 兼 CDO スチュアート・ヒューズ氏
関連リソースeBookERP のデータを活用するWeb セミナーデータ＋AI で製造業の予知保全を向上させるeBookインテリジェントな製造を推進する 4 つのちから無料お試し・その他ご相談を承りますお客さまのビジネスゴールをお聞かせください。Databricks のサービスチームがお役に立ちます。Databricks 無料トライアルご相談・お問い合わせ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ 採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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https://www.databricks.com/blog/2022/03/03/hyper-personalization-accelerator-for-banks-and-fintechs-using-credit-card-transactions.html
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Hyper-Personalization Accelerator for Banks and Fintechs Using Credit Card Transactions - 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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NuBank's success story as an eight-year old startup becoming Latin America's most valuable bank is not an isolated case; over 280 other fintechs unicorns are also willing to disrupt the entire payment industry. As noted in the Financial Conduct Authority (FCA) study, "There are signs that some of the historic advantages of large banks may be starting to weaken through innovation, digitization and changing consumer behavior." Faced with the choice of either disrupting or being disrupted, many traditional financial services institutions (FSIs) like JP Morgan Chase have recently announced significant strategic investments to compete with fintech companies on their own grounds – on the cloud, using data and artificial intelligence (AI).Given the volume of data required to drive advanced personalization, the complexity of operating AI from experiments (proof of concepts/POCs) to enterprise scale data pipelines, combined with strict data and privacy regulations on the use of customer data on cloud infrastructure, Lakehouse for Financial Services has quickly emerged as the strategic platform for many disruptors and incumbents alike to accelerate digital transformation and provide millions of customers with personalized insights and enhanced banking experiences (see how HSBC is reinventing mobile banking with AI).In our previous solution accelerator, we showed how to identify brands and merchants from credit card transactions. In our new solution accelerator (inspired from the 2019 study of Bruss et. al. and from our experience working with global retail banking institutions), we capitalized on that work to build a modern hyper-personalization data asset strategy that captures a full picture of the consumer and goes beyond traditional demographics, income, product and services (who you are) and extends to transactional behavior and shopping preferences (how you bank). As a data asset, the same can be applied to many downstream use cases, such as loyalty programs for online banking applications, fraud prevention for core banking platforms or credit risk for "buy now pay later" (BNPL) initiatives.Transactional contextWhile the common approach to any segmentation use case is a simple clustering model, there are only a few off-the-shelf techniques. Alternatively, when converting data from its original archetype, one can access a wider range of techniques that often yield unexpected results. In this solution accelerator, we convert our original card transaction data into graph paradigm and leverage techniques originally designed for Natural Language Processing (NLP).Similar to NLP techniques where the meaning of a word is defined by its surrounding context, a merchant's category can be learned from its customer base and the other brands that their consumers support. In order to build this context, we generate "shopping trips" by simulating customers walking from one shop to another, up and down our graph structure. The aim is to learn "embeddings," a mathematical representation of the contextual information carried by the customers in our network. In this example, two merchants contextually close to one another would be embedded into large vectors that are mathematically close to one another. By extension, two customers exhibiting the same shopping behavior will be mathematically close to one another, paving the way for a more advanced customer segmentation strategy.Merchant embeddingsWord2Vec was developed by Tomas Mikolov, et. al. at Google to make the neural network training of the embedding more efficient, and has since become the de facto standard for developing pre-trained word embedding algorithms. In our solution, we will use the default wordVec model from the Apache Spark™ ML API that we train against our shopping trips defined earlier.
from pyspark.ml.feature import Word2Vec
with mlflow.start_run(run_name='shopping_trips') as run:
word2Vec_model = Word2Vec() \
.setVectorSize(255) \
.setWindowSize(3) \
.setMinCount(5) \
.setInputCol('walks') \
.setOutputCol(vectors) \
.fit(shopping_trips)
mlflow.spark.log_model(word2Vec_model, "model")
The most obvious way to quickly validate our approach is to eyeball its results and apply domain expertise. In this example of brands like "Paul Smith", our model can find Paul Smiths' closest competitors to be "Hugo Boss", "Ralph Lauren" or "Tommy Hilfiger."We did not simply detect brands within the same category (i.e. fashion industry) but detected brands with a similar price tag. Not only could we classify different lines of businesses using customer behavioral data, but our customer segmentation could also be driven by the quality of goods they purchase. This observation corroborates the findings by Bruss et. al.Merchant clusteringAlthough the preliminary results were troubling, there might be groups of merchants more or less similar than others that we may want to identify further. The easiest way to find those significant groups of merchants/brands is to visualize our embedded vector space into a 3D plot. For that purpose, we apply machine learning techniques like Principal Component Analysis (PCA) to reduce our embedded vectors into 3 dimensions.Using a simple plot, we could identify distinct groups of merchants. Although these merchants may have different lines of business, and may seem dissimilar at first glance, they all have one thing in common: they attract a similar customer base. We can better confirm this hypothesis through a clustering model (KMeans).Transactional fingerprintsOne of the odd features of the word2vec model is that sufficiently large vectors could still be aggregated while maintaining high predictive value. To put it another way, the significance of a document could be learned by averaging the vector of each of its word constituents (see whitepaper from Mikolov et. al.). Similarly, customer spending preferences can be learned by aggregating vectors of each of their preferred brands. Two customers having similar tastes for luxury brands, high-end cars and fine liquor would theoretically be close to one another, hence belonging to the same segment.
customer_merchants = transactions \
.groupBy('customer_id') \
.agg(F.collect_list('merchant_name').alias('walks'))
customer_embeddings = word2Vec_model.transform(customer_merchants)
It is worth mentioning that such an aggregated view would generate a transactional fingerprint that is unique to each of our end consumers. Although two fingerprints may share similar traits (same shopping preferences), these unique signatures can be used to track unique individual customer behaviors over time.When a signature drastically differs from previous observations, this could be a sign of fraudulent activities (e.g. sudden interest for gambling companies). When signature drifts over time, this could be indicative of life events (having a newborn child). This approach is key to driving hyper-personalization in retail banking: the ability to track customer preferences against real-time data will help banks provide personalized marketing and offers, such as push notifications, across various life events, positive or negative.Customer segmentationAlthough we were able to generate some signal that offers great predictive value to customer behavioral analytics, we still haven't addressed our actual segmentation problem. Borrowing from retail counterparts that are often more advanced when it comes to customer 360 use cases including segmentation, churn prevention or customer lifetime value, we can use a different solution accelerator from our Lakehouse for Retail that walks us through different segmentation techniques used by best-in-class retail organizations.Following retail industry best practices, we were able to segment our entire customer base against 5 different groups exhibiting different shopping characteristics.While cluster #0 seems to be biased towards gambling activities (merchant category 4 in the above graph), another group is more centered around online businesses and subscription-based services (merchant category 6), probably indicative of a younger generation of customers. We invite our readers to complement this view with additional data points they already know about their customers (original segments, products and services, average income, demographics, etc.) to better understand each of those behavioral driven segments and its impact for credit decisioning, next-best action, personalized services, customer satisfaction, debt collection or marketing analytics.Closing thoughtsIn this solution accelerator, we have successfully applied concepts from the world of NLP to card transactions for customer segmentation in retail banking. We also demonstrated the relevance of the Lakehouse for Financial Services to address this challenge where graph analytics, matrix calculation, NLP, and clustering techniques must all be combined into one platform, secured and scalable. Compared to traditional segmentation methods easily addressed through the world of SQL, the disruptive future of segmentation builds a fuller picture of the consumer and can only be solved with data + AI, at scale and in real time.Although we've only scratched the surface of what was possible using off-the-shelf models and data at our disposal, we proved that customer spending patterns can more effectively drive hyper-personalization than demographics, opening up an exciting range of new opportunities from cross-sell/upsell and pricing/targeting activities to customer loyalty and fraud detection strategies.Most importantly, this technique allowed us to learn from new-to-bank individuals or underrepresented consumers without a known credit history by leveraging information from others. With 1.7 billion adults worldwide who do not have access to a bank account according to the World Economic Forum, and 55 million underbanked in the US alone in 2018 according to the Federal Reserve, such an approach could pave the way towards a more customer-centric and inclusive future for retail banking.Try the accelerator notebooks on Databricks to test your customer 360 data asset strategy today and contact us to learn more about how we have helped customers with similar use cases.Try Databricks for freeGet StartedRelated postsImproving Customer Experience With Transaction EnrichmentMay 10, 2021 by Milos Colic in Engineering Blog
The retail banking landscape has dramatically changed over the past five years with the accessibility of open banking applications, mainstream adoption of Neobanks...
4 Ways AI Can Future-proof Financial Services’ Risk and ComplianceSeptember 16, 2021 by Fahmid Kabir and Antoine Amend in Industries
Learn more about Smarter risk and compliance on our new hub. The core function of a bank is to protect assets, identify risks...
A Data-driven Approach to Environmental, Social and GovernanceJuly 10, 2020 by Antoine Amend in Engineering Blog
The future of finance goes hand in hand with social responsibility, environmental stewardship and corporate ethics. In order to stay competitive, Financial Services...
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Data Science | 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
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https://www.databricks.com/dataaisummit/speaker/julie-ferris/#
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Julie Ferris - 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 ExperiencePricingJulie FerrisVice President, Commercial Optimization at Definitive HealthcareBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
|
https://www.databricks.com/dataaisummit/speaker/rakesh-kumar
|
Rakesh 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 ExperiencePricingRakesh KumarStaff Software Engineer at Lyft IncBack to speakersRakesh Kumar is a staff software engineer on the Realtime Optimization Platform team at Lyft. He started his career as an embedded software engineer for mobile devices; later he moved to server-side engineer to tackle bigger challenges in distributed systems. His interests include machine learning and streaming systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
|
https://www.databricks.com/dataaisummit/speaker/suneel-konidala
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Suneel Konidala - 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 ExperiencePricingSuneel KonidalaSr. Manager at AccentureBack to speakersSuneel is an accomplished leader in Data space for more than two decades. He is a lead partner champion at Accenture's Databricks practice. Suneel is well versed in multiple data and cloud 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.
|
https://www.databricks.com/dataaisummit/speaker/balaji-ramanujam
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Balaji Ramanujam - 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 ExperiencePricingBalaji RamanujamAVP - Senior Principal Technology Architect at InfosysBack to speakersBalaji is Head of Industry Architecture - Data and AI North America (USA & Canada), with 23 years of experience in Information Technology and experience in Healthcare / Life sciences , Banking & Retail industry. He is a Data Technologist with flair and passion for solving complex data problems, helping business build connections and eco-systems (Next generation data trend). He is architecture Leader for North America on Cloud and Data Management , Data engineering and ML engineering technologies with focus on creating Business Platforms and creating industry solutions.
He has strong skills in Cloud Data Architecture, Enterprise ML, Data Modeling, design, development and implementation of ETL & BI Analytics solutions. Worked on large programs involving complex business requirements and different business teams. He has played key roles in initiating and enabling new projects. Technical Architect /Consultant / advisor to multiple BI Projects - providing inputs from solution architecture to data model to reporting layer - to enhance the efficiency of a solution.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
|
https://www.databricks.com/dataaisummit/speaker/erin-boelkens
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Erin Boelkens - 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 ExperiencePricingErin BoelkensVP of Product at LiveRampBack to speakersErin Boelkens is Vice President of Product at LiveRamp (NYSE: RAMP). In this role, she oversees LiveRamp solutions that enable clients to manage data assets in a safe and secure way across identity, business development, addressability, healthcare, and data management. Previously, Erin was LiveRamp’s VP of Engineering and Head of Global Identity Engineering, where she led a team of creative and innovative engineers providing industry-leading identity products across offline and online channels. Erin joined the company in 2018 after spending 13 years in engineering, product and data science at Acxiom (Nasdaq: ACXM). Erin holds a bachelor’s degree in computer information systems and a master’s of science in management information systems from Arkansas State University. She is also certified as a Scrum Product Owner and a Scrum Master from the Scrum Alliance, as well as Marketing certification from Pragmatic Marketing. She resides in Little Rock, Arkansas.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
|
https://www.databricks.com/dataaisummit/speaker/ivan-peng/#
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Ivan Peng - 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 ExperiencePricingIvan PengSoftware Engineer at DoorDashBack to speakersIvan is a software engineer on the data infrastructure team at DoorDash. His team is responsible for providing the foundation of data and ensuring that it is accurate and delivered in a timely manner. Prior to DoorDash, Ivan was at Nextdoor on the Data Platform team, focusing on experimentation and building a data platform for privacy and compliance. In his spare time, Ivan enjoys playing ultimate frisbee, geeking out about sports analytics, and biking to distant places in lieu of driving.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.
|
https://www.databricks.com/blog/2021/11/16/evolution-of-the-sql-language-at-databricks-ansi-standard-by-default-and-easier-migrations-from-data-warehouses.html
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Evolution of the SQL language at Databricks: ANSI standard by default and easier migrations from data warehouses - 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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SELECT
o_orderstatus || ' ' || o_shippriority as order_info
FROM
orders;
The FILTER clause, which has been in the SQL standard since 2003, limits rows that are evaluated during an aggregation. Most data warehouses require a complex CASE expression nested within the aggregation instead:
SELECT
COUNT(DISTINCT o_orderkey) as order_volume,
COUNT(DISTINCT o_orkerkey) FILTER (WHERE o_totalprice > 100.0) as big_orders <span style="color: #a56319;">-- using rows that pass the predicate</span>
FROM orders;
SQL user-defined functions (UDFs) make it easy to extend and modularize business logic without having to learn a new programming language:
CREATE FUNCTION inch_to_cm(inches DOUBLE)
RETURNS DOUBLE RETURN 2.54 * inches;
SELECT inch_to_cm(5); <span style="color: #a56319;">-- returns 12.70</span>
Compatibility with other data warehousesDuring migrations, it is common to port hundreds or even thousands of queries to Databricks SQL. Most of the SQL you have in your existing data warehouse can be dropped in and will just work on Databricks SQL. To make this process simpler for customers, we continue to add SQL features that remove the need to rewrite queries.For example, a new QUALIFY clause to simplify filtering window functions makes it easier to migrate from Teradata. The following query finds the five highest-spending customers in each day:
SELECT
o_orderdate,
o_custkey,
RANK(SUM(o_totalprice)) OVER (PARTITION BY o_orderdate ORDER BY SUM(o_totalprice) DESC) AS rank
FROM orders
GROUP BY o_orderdate, o_custkey
QUALIFY rank -- applies after the window function
We will continue to increase compatibility features in the coming months. If you want us to add a particular SQL feature, don’t hesitate to reach out.Quality control for SQLWith the adoption of the ANSI SQL dialect, Databricks SQL now proactively alerts analysts to problematic queries. These queries are uncommon but they are best caught early so you can keep your lakehouse fresh and full of high-quality data. Below is a selection of such changes (see our documentation for a full list).Invalid input values when casting a STRING to an INTEGERArithmetic operations that cause an overflowDivision by zeroEasily and efficiently query and transform JSONIf you are an analyst or data engineer, chances are you have worked with unstructured data in the form of JSON. Databricks SQL natively supports ingesting, storing and efficiently querying JSON. With this release, we are happy to announce improvements that make it easier than ever for analysts to query JSON.Let’s take a look at an example of how easy it is to query JSON in a modern manner. In the query below, the raw column contains a blob of JSON. As demonstrated, we can query and easily extract nested fields and items from an array while performing a type conversion:
SELECT
raw:customer.full_name, <span style="color: #a56319;">-- nested field</span>
raw:customer.addresses[0], <span style="color: #a56319;">-- array</span>
raw:customer.age::integer, <span style="color: #a56319;">-- type cast</span>
FROM customer_data;
With Databricks SQL you can easily run these queries without sacrificing performance or by having to extract the columns out of JSON into separate tables. This is just one way in which we are excited to make life easier for analysts.Simple, elegant SQL for common tasksWe have also spent time doing spring cleaning on our SQL support to make other common tasks easier. There are too many new features to cover in a blog post, but here are some favorites.Case-insensitive string comparisons are now easier:
SELECT
*
FROM
orders
WHERE
o_orderpriority ILIKE '%urgent'; <span style="color: #a56319;">-- case insensitive string comparison</span>
Shared WINDOW frames save you from having to repeat a WINDOW clause. Consider the following example where we reuse the win WINDOW frame to calculate statistics over a table:
SELECT
round(avg(o_totalprice) OVER win, 1) AS price,
round(avg(o_totalprice) OVER win, 1) AS avg_price,
min(o_totalprice) OVER win AS min_price,
max(o_totalprice) OVER win AS max_price,
count(1) OVER win AS order_count
FROM orders
<span style="color: #a56319;">-- this is a shared WINDOW frame</span>
WINDOW win AS (ORDER BY o_orderdate ROWS BETWEEN 2 PRECEDING AND 2 FOLLOWING);
Multi-value INSERTs make it easy to insert multiple values into a table without having to use the UNION keyword, which is common most other data warehouses:
CREATE TABLE employees
(name STRING, dept STRING, salary INT, age INT);
<span style="color: #a56319;">-- this is a multi-valued INSERT</span>
INSERT INTO employees
VALUES ('Lisa', 'Sales', 10000, 35),
('Evan', 'Sales', 32000, 38),
('Fred', 'Engineering', 21000, 28);
Lambda functions are parameterized expressions that can be passed to certain SQL functions to control their behavior. The example below passes a lambda to the transform function, concatenating together the index and values of an array (themselves an example of structured types in Databricks SQL).
<span style="color: #a56319;">-- this query returns ["0: a","1: b","2: c"]</span>
SELECT
transform(
array('a','b','c'),
(x, i) -> i::string || ': ' || x <span style="color: #a56319;">-- this is a lambda function</span>
);
Update data easily with standard SQLData is rarely static, and it is common to to update a table based on changes in another table. We are making it easy for users to deduplicate data in tables, create slowly-changing data and more with a modern, standard SQL syntax.Let’s take a look at how easy it is to update a customers table, merging in new data as it arrives:
MERGE INTO customers <span style="color: #a56319;">-- target table</span>
USING customer_updates <span style="color: #a56319;">-- source table with updates</span>
ON customers.customer_id = customer_updates.customer_id
WHEN MATCHED THEN
UPDATE SET customers.address = customer_updates.address
Needless to say, you do not sacrifice performance with this capability as table updates are blazing fast. You can find out more about the ability to update, merge and delete data in tables here.Taking it for a spinWe understand language dialect changes can be disruptive. To facilitate the rollout, we are happy to announce a new feature, channels, to help customers safely preview upcoming changes.When you create or edit a SQL endpoint, you can now choose a channel. The “current” channel contains generally available features while the preview channel contains upcoming features like the ANSI SQL dialect.To test out the ANSI SQL dialect, click SQL Endpoints in the left navigation menu, click on an endpoint and change its channel. Changing the channel will restart the endpoint, and you can always revert this change later. You can now test your queries and dashboards on this endpoint.You can also test the ANSI SQL dialect by using the SET command, which enables it just for the current session:
SET ansi_mode = true; <span style="color: #a56319;">-- only use this setting for testing</span>
SELECT CAST('a' AS INTEGER);
Please note that we do NOT recommend setting ANSI_MODE to false in production. This parameter will be removed in the future, hence you should only set it to FALSE temporarily for testing purposes.The future of SQL at Databricks is open, inclusive and fastDatabricks SQL already set the world record in performance, and with these changes, it is standards compliant. We are excited about this milestone, as it is key in dramatically improving usability and simplifying workload migration from data warehouses over to the lakehouse platform.Please learn more about changes included in the ANSI SQL dialect. Note that the ANSI dialect is not enabled as default yet for existing or new clusters in the Databricks data science and engineering workspace. We are working on that next.Try Databricks for freeGet StartedRelated postsIntroducing SQL User-Defined FunctionsOctober 20, 2021 by Serge Rielau and Allison Wang in Platform Blog
A user-defined function (UDF) is a means for a user to extend the native capabilities of Apache Spark™ SQL. SQL on Databricks has s...
Databricks SQL: Delivering a Production SQL Development Experience on the Data LakeSeptember 30, 2021 by Miranda Luna and Cyrielle Simeone in Platform Blog
Databricks SQL is now generally available on AWS and Azure. Databricks SQL (DB SQL) is a simple and powerful SQL analytics platform for...
New Performance Improvements in Databricks SQLSeptember 8, 2021 by Reynold Xin, Can Efeoglu and Cyrielle Simeone in Platform Blog
Databricks SQL is now generally available on AWS and Azure. Originally announced at Data + AI Summit 2020 Europe, Databricks SQL lets you...
Evolution of the Sql Language at Databricks: Ansi Standard by Default and Easier Migrations from Data WarehousesNovember 16, 2021 by Serge Rielau, Shant Hovsepian and Reynold Xin in Platform Blog
Databricks SQL is now generally available on AWS and Azure. Today, we are excited to announce that Databricks SQL will use the ANSI...
See all Platform Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers
at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc.
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https://www.databricks.com/dataaisummit/speaker/sanket-amin
|
Sanket Amin - 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 ExperiencePricingSanket AminSenior Manager of CAS Data Science and Analytics at Collins AerospaceBack to speakersSanket Amin’s data analysis journey starts with research and development of vibration based predictive algorithms for jet engines. This naturally led him to investigate opportunities to analyze large volumes and other aircraft data signals. He has worked on projects with many important aerospace companies and organizations including NASA, GE, Pratt and Whitney, NAVAIR, and AFRL. He currently leads a team a data science team at Collins Aerospace’s Connected Aviation Solutions business unit.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/demand-forecasting
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What is Demand Forecasting?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 NOWDemand ForecastingAll>Demand ForecastingTry Databricks for freeGet StartedWhat is demand forecasting?Demand forecasting is the process of projecting consumer demand (equating to future revenue). Specifically, it is projecting the assortment of products shoppers will buy using quantitative and qualitative data.Retailers are facing a trillion-dollar problem due to unavailable products at the time consumers demand them. Poor demand forecasting is causing companies to put the wrong product on the shelf, or an even bigger issue, to have in-store stock outagesHow can Lakehouse for Retail enable demand forecasting?Lakehouse for Retail enables real-time access to data. Moving from batch-oriented access, analysis, and compute will allow data to be “always-on,” therefore driving real-time decisions and business intelligence. The Lakehouse uses technologies that include Delta, Delta Live Tables, Autoloader, and Photon to enable organizations to make data available for real-time decisions.Lakehouse for Retail supports the largest data jobs at nearly real-time intervals. For example, customers are bringing nearly 400 million events per day from transactional log systems at 15-second intervals. Because of the disruption to reporting and analysis that occurs during data processing, most retail customers load data to their data warehouse during a nightly batch. Some companies are even loading data weekly or monthly.Lakehouse event-driven architecture provides a simpler method of ingesting and processing batch and streaming data than legacy approaches, such as lambda architectures. This architecture handles the change data capture and provides ACID compliance to transactions.Delta Live Tables simplifies the creation of data pipelines and automatically builds in lineage to assist with ongoing management.The Lakehouse allows for true real-time stream ingestion of data, and even analytics on streaming data. Data warehouses require the extraction, transformation, loading, and then additional extraction from the data warehouse to perform any analytics.Photon provides record-setting query performance, enabling users to query even the largest data sets to power real-time decisions in BI tools.What data sources are needed for successful demand forecasting?Demand forecasting is an integral part of delivering products to consumers. To successfully deliver products to consumers, retailers must work with manufacturers in these operational processes and use cases: Sales and Operations Planning (S&OP), supply chain optimization, inventory control and optimization, and production scheduling. Data originates from several sources that feeds the demand forecasting models, including:
Point of sale: sales transaction is in the form of structured real-time dataHistorical demand: Historical demand can be housed in enterprise resource planning systems (SAP) and usually structured in batch formatExternal data: Social feeds, news, and competitor information is usually in a real-time unstructured formatClick-stream: semi-structured in real-timeExternal data: even weather can be a factor in determining demand (think of tornado or hurricane)Additional ResourcesCollaborating Across the Retail Value Chain with Data and AIImproving On-Shelf Availability for Items With AI Out of Stock ModelingHow Starbucks forecasts demand at scaleBack 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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