Almost every dataset hides a location, the ultimate universal foreign key. Yet geographic data is often overlooked, poorly joined, or reduced to points on a map. The relationships it could reveal stay hidden. The first half of this session covers shaping and engineering spatial data in Microsoft Fabric using SQL and Python, so raw coordinates become geography you can join on, measure, and trust.

The second half covers how that data gets consumed. We'll bring it into interactive maps, Fabric apps, and AI agents that answer proximity and boundary questions in natural language. You'll see why the modeling work behind a good map is the same work that lets an agent reason about where things are.

You'll learn how to:
- Convert coordinates and query spatial data
- Run spatial joins and proximity analysis
- Build custom geographic boundaries
- Structure spatial data for maps, apps, and agents

No GIS background needed!