<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Yestino - The Signal · Databricks</title><link>https://yestino.com/entities/databricks-b15347</link><description>Every event involving Databricks</description><language>en</language><atom:link href="https://yestino.com/entities/databricks-b15347/feed.xml" rel="self" type="application/rss+xml"/><item><title>Introducing Governance Hub: Intelligent, account-level governance over your Databricks estate</title><link>https://yestino.com/events/introducing-governance-hub-intelligent-account-level-governa-1b1d8e</link><guid isPermaLink="true">https://yestino.com/events/introducing-governance-hub-intelligent-account-level-governa-1b1d8e</guid><pubDate>Wed, 26 Aug 2026 03:00:00 GMT</pubDate><description>Governance Hub is a new account-level experience that gives administrators and governance teams a unified view of data health, AI usage, and cost, with agentic…
Sources: Databricks Blog</description></item><item><title>Leveraging Databricks to Support FISC Security Guidelines</title><link>https://yestino.com/events/leveraging-databricks-to-support-fisc-security-guidelines-3632b2</link><guid isPermaLink="true">https://yestino.com/events/leveraging-databricks-to-support-fisc-security-guidelines-3632b2</guid><pubDate>Wed, 26 Aug 2026 00:00:00 GMT</pubDate><description>Financial institutions in Japan can configure the Databricks Platform to support requirements from the Japanese Center for Financial Industry Systems (FISC) Se…
Sources: Databricks Blog</description></item><item><title>How Capital Markets Finance Protects Balance Sheet Returns</title><link>https://yestino.com/events/how-capital-markets-finance-protects-balance-sheet-returns-2bfa5e</link><guid isPermaLink="true">https://yestino.com/events/how-capital-markets-finance-protects-balance-sheet-returns-2bfa5e</guid><pubDate>Tue, 25 Aug 2026 20:00:01 GMT</pubDate><description>An insurer settles a claim months after the loss.
Sources: Databricks Blog</description></item><item><title>Choosing Data Governance Tools for Enterprise Data Governance</title><link>https://yestino.com/events/choosing-data-governance-tools-for-enterprise-data-governanc-ad0df5</link><guid isPermaLink="true">https://yestino.com/events/choosing-data-governance-tools-for-enterprise-data-governanc-ad0df5</guid><pubDate>Tue, 25 Aug 2026 16:17:44 GMT</pubDate><description>Data governance tools explained: core capabilities, tool types, and a practical framework for evaluating and choosing the right one for your stack.
Sources: Databricks Blog</description></item><item><title>Data Mesh vs. Data Fabric: Key Differences and How the Lakehouse Resolves the Debate</title><link>https://yestino.com/events/data-mesh-vs-data-fabric-key-differences-and-how-the-lakehou-8a0ec2</link><guid isPermaLink="true">https://yestino.com/events/data-mesh-vs-data-fabric-key-differences-and-how-the-lakehou-8a0ec2</guid><pubDate>Tue, 25 Aug 2026 16:05:34 GMT</pubDate><description>Data mesh decentralizes data ownership; data fabric automates integration.
Sources: Databricks Blog</description></item><item><title>Modernizing SQL ETL in Lakehouse with Declarative Patterns</title><link>https://yestino.com/events/modernizing-sql-etl-in-lakehouse-with-declarative-patterns-ba8460</link><guid isPermaLink="true">https://yestino.com/events/modernizing-sql-etl-in-lakehouse-with-declarative-patterns-ba8460</guid><pubDate>Tue, 25 Aug 2026 15:00:00 GMT</pubDate><description>Databricks brings declarative ETL to the SQL Editor with APPEND, AUTO CDC, and REPLACE WHERE flows in Lakehouswe.
Sources: Databricks Blog</description></item><item><title>Open Table Formats Explained: Iceberg vs. Delta vs. Hudi</title><link>https://yestino.com/events/open-table-formats-explained-iceberg-vs-delta-vs-hudi-e8afaf</link><guid isPermaLink="true">https://yestino.com/events/open-table-formats-explained-iceberg-vs-delta-vs-hudi-e8afaf</guid><pubDate>Tue, 25 Aug 2026 07:37:09 GMT</pubDate><description>Open table formats bring ACID transactions, schema evolution, and time travel to data lakes.
Sources: Databricks Blog</description></item><item><title>Run, debug, and scale Databricks workloads from your local IDE</title><link>https://yestino.com/events/run-debug-and-scale-databricks-workloads-from-your-local-ide-93120e</link><guid isPermaLink="true">https://yestino.com/events/run-debug-and-scale-databricks-workloads-from-your-local-ide-93120e</guid><pubDate>Mon, 24 Aug 2026 17:01:08 GMT</pubDate><description>Customers can now connect local IDEs to Databricks to interactively run workloads and edit workspace files.
Sources: Databricks Blog</description></item><item><title>How Databricks Uses AI to Accelerate Incident Investigation</title><link>https://yestino.com/events/how-databricks-uses-ai-to-accelerate-incident-investigation-745eda</link><guid isPermaLink="true">https://yestino.com/events/how-databricks-uses-ai-to-accelerate-incident-investigation-745eda</guid><pubDate>Mon, 24 Aug 2026 17:00:00 GMT</pubDate><description>Discover how Databricks uses AI SRE to accelerate incident investigation.
Sources: Databricks Blog</description></item><item><title>Relational vs Non-Relational Database: Choosing the Right Data Store</title><link>https://yestino.com/events/relational-vs-non-relational-database-choosing-the-right-dat-3ca77c</link><guid isPermaLink="true">https://yestino.com/events/relational-vs-non-relational-database-choosing-the-right-dat-3ca77c</guid><pubDate>Mon, 24 Aug 2026 16:56:45 GMT</pubDate><description>Choosing between relational and non-relational databases is one of the most consequential architectural decisions teams make when building data systems, and th…
Sources: Databricks Blog</description></item><item><title>Transactional Vs Analytical Database: Choosing OLTP, OLAP, or Hybrid</title><link>https://yestino.com/events/transactional-vs-analytical-database-choosing-oltp-olap-or-h-25cbe0</link><guid isPermaLink="true">https://yestino.com/events/transactional-vs-analytical-database-choosing-oltp-olap-or-h-25cbe0</guid><pubDate>Mon, 24 Aug 2026 16:53:46 GMT</pubDate><description>Transactional and analytical databases serve opposite workloads.
Sources: Databricks Blog</description></item></channel></rss>