Microsoft Fabric Data Agents can query your semantic models, but do they truly understand your business?

Traditional semantic models are excellent at organizing data for reporting and analytics. AI, however, needs more than tables, measures, and relationships. It needs business meaning.

In this session, you'll discover how semantic models and ontologies work together to create a knowledge layer for Microsoft Fabric. By adding shared business definitions, context, and relationships, ontologies help Data Agents reduce ambiguity, reason more effectively, and deliver more trustworthy answers.

Through practical demonstrations, we'll show how business knowledge can enrich semantic models and enable AI experiences that understand not just your data, but the business concepts behind it.

Key takeaways

Why AI needs business context, not just data structures
How ontologies help Data Agents understand business concepts and relationships
How semantic models and ontologies complement each other
How to build more trustworthy and scalable AI solutions in Fabric

Bottom line:
Semantic models help AI find data.
Ontologies help AI understand the business. Together, they create AI-ready analytics.

Audience & prerequisites
Whether you're a Fabric architect, BI professional, data engineer, or AI enthusiast, You'll leave with practical patterns, architectural guidance, and techincal examples for using Semantic Models, Ontologies to empower data agents.