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Azure Databricks at Data + AI Summit 2026 featuring Industry Leaders and Partners
Kiriana Stukas
- Source
- Databricks
- Published
- Added to Yomu
Summary
Data + AI Summit 2026 brings Databricks and Microsoft leaders, partners, and customers together June 15–18, with in-person and virtual programming focused on Azure Databricks. The collaboration presents Azure Databricks as a first-party Microsoft offering for unifying data, analytics, and AI on a secure, scalable foundation, with sessions covering ecosystem integration, federated analytics, governance, modernization, and AI applications. One technical example introduces zero-copy federation between Azure Data Manager for Energy and Databricks compute, preserving ADME as the source of truth while avoiding large-scale data copies. Another shows Unity Catalog External Locations extending governed access to Microsoft OneLake without ETL pipelines, while customer sessions describe Apache Iceberg and Apache Spark integration, fragmented data consolidation, and production-grade finance workflows using Azure Document Intelligence.
Context
Data + AI Summit 2026 is presented as a forum for learning how organizations use Azure Databricks to modernize data estates, scale AI, and build governed data and AI applications, analytics, and agents on Azure.
Approach / What changed
The event combines keynote and breakout sessions, technical demonstrations, customer examples, partner presentations, and executive forums. Topics include zero-copy federation, Unity Catalog governance across Microsoft OneLake, open lakehouse integration with Apache Iceberg and Apache Spark, and AI automation workflows using Azure Document Intelligence.
Takeaways
- A jointly developed zero-copy path brings Databricks compute directly to Azure Data Manager for Energy data, keeping ADME as the single source of truth while avoiding downstream copies.
- Unity Catalog External Locations are being extended to Microsoft OneLake, enabling governed reads and writes without setting up ETL pipelines and pointing toward future on-premises storage support.
- GEODIS integrated Azure Databricks with legacy Cloudera infrastructure using Apache Iceberg and Apache Spark, avoiding a big-bang migration while addressing cross-catalog performance and data quality validation.