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Delta lakehouse12/14/2023 ![]() Governance for everything – Unity Catalog, which harmonizes access to all analytic data across the enterprise along with federated mesh and monitoring tools and then the Lakehouse 3.0 focus, which unifies all the different formats such as Delta, Hudi and Iceberg - a feature announcement that was very well-received by developers.A platform for gen AI app development – The MosaicML acquisition as a way to make building and fine-tuning custom models simpler and more cost-effective Vector Search, which makes it easy to find relevant content to feed to generative models and Model Serving and Unity Catalog for AI where AI features and functions are integrated.Democratization of analytics – Lakehouse IQ uses large language models to infer some of the business meaning from technical data artifacts like a semantic layer would, marketplace is focused on data sharing with partnerships like Twilio, Dell and Oracle of all firms…and Lakehouse Apps to enable the safe running of apps.The three big themes of the event are seen above with several announcements and innovation areas of focus shown beneath each one. Databricks Data+AI Summit focused on three high-level themes To do so, we tap the knowledge of three experts who attended the event, CUBE analysts Rob Strechay and George Gilbert and AI market maven Andy Thurai of Constellation Research Inc. In this Breaking Analysis, we follow up last week’s research by connecting the dots on the emerging tech stack we see forming from Databricks, with an emphasis on how the company is approaching generative AI, unification and governance - and what it means for customers. But they have to access external operational applications to take action. ![]() Developers can build analytic applications across heterogeneous data, like Palantir Technologies Inc. ![]() Databricks likely has a similar lead in terms of unifying all types of analytic data – business intelligence, predictive analytics and generative artificial intelligence. when it won the database market, that perform analysis and take action. Developers can build applications on one platform, like Oracle Corp. Rather, Snowflake is likely years ahead in terms of operationalizing data. In our view, the market size justifies the current enthusiasm seen around both platforms, but it’s unlikely that either company has a knockout blow for the other. are attacking the problem from different perspectives. While customers demand a unified platform to access all their data, Databricks Inc. ![]() The recent Databricks Data+AI Summit attracted a large audience and, like Snowflake Summit, featured a strong focus on large language models, unification and bringing AI to the data. With George Gilbert, Rob Strechay and Andy Thurai ![]()
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