In this session, we follow an end-to-end journey from development to decision-making. We start with transactional and near-real-time workloads in SQL Database in Fabric, show how those datasets flow into Fabric Data Warehouse for governed analytics, and then connect both worlds to AI-ready experiences – including intelligent planning and forecasting scenarios enabled by the new Planning capabilities in Fabric.

We’ll dive into:

Where Fabric Data Warehouse and SQL Database in Fabric overlap – and where each clearly shines

How to design the interfaces between the two: data movement, mirroring/shortcuts, schemas, and semantic alignment

How the “SQL is ready for AI” story changes architecture decisions: vector search, agentic patterns, and “chat with your data” based on a shared semantic layer

How Planning in Fabric can sit on top of this stack to build intelligent planning & forecast models that use both operational and analytical data

It’s a pragmatic architecture session from someone who has already built multiple data platforms and seen the limits of classic “modern data estate” patterns. If you want to understand how to evolve your platform into an intelligent data estate using Fabric Data Warehouse and SQL Database in Fabric together, this session is for you.

After this session, attendees will be able to:

(1) Position Fabric Data Warehouse vs. SQL Database in Fabric in their architecture – understanding strengths, limitations, and typical workload patterns for each.

(2) Design a “better together” architecture, including data flows and interfaces between SQL Database in Fabric and Fabric Data Warehouse.

(3) Leverage SQL’s new AI-ready capabilities in combination with Fabric (e.g., agents, “chat with your data”, intelligent applications) instead of treating SQL only as a system of record.

(4) Use Fabric’s Planning capabilities on top of Data Warehouse + SQL Database in Fabric to implement intelligent planning & forecasting scenarios.