Matthew Hicks

As data volumes grow, managing an organization-wide data estate is increasingly complex. This session will deep dive into the latest capabilities to unify your data in OneLake via shortcuts and mirroring.

Enterprise data is fragmented, and AI pays the price. See how Microsoft OneLake makes Apache Iceberg a first-class citizen, letting Fabric, Databricks, Snowflake, Clickhouse, Spark, and Trino read and write the same tables with no copies or ETL.

Whether you’re running advanced analytics or developing AI applications, Snowflake and Microsoft have the platform and solutions to make your job easier. In this session, we’ll show you how you can interoperate on one copy of data between Microsoft Fabric OneLake and Snowflake via open source Apache Iceberg, without the need for data replication. You’ll also learn how to enhance your enterprise AI apps and workflows developed with knowledge from Snowflake. Finally, we’ll show you how you can make AI accessible for all your users by leveraging Snowflake Cortex Agents within Microsoft 365 Copilot and Microsoft Teams.

This hands on workshop walks through building a modern data architecture with shared storage, based on Iceberg. As data volumes increase and AI workloads proliferate, copying and ETL’ing data across systems is no longer sustainable.

OneLake enables true interoperability, enabling you to write Iceberg and Delta tables once and query them anywhere. Learn how OneLake supports data governance, Spark DML and lifecycle management while exposing the same tables to Snowflake, Athena, Glue, Fabric engines, Power BI, and AI Agents without copies.

In this session, you’ll learn how to unify your organization’s entire data estate in OneLake and carry out a full range of analytics tasks on a single copy of your data.