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- Learn to design gold layers, configure Prep for AI features, and connect semantic models to enterprise ontology with Fabric IQ so that Copilot and AI agents deliver accurate, business-relevant insights.
By the end of this module, you're able to:
- Describe how AI systems consume data and metadata from semantic models.
- Design gold layers with AI-friendly naming, documentation, and structure.
- Configure Prep for AI features in a semantic model, including verified answers and AI instructions.
- Explain how semantic models connect to enterprise ontology in Fabric IQ.
- Validate AI readiness through testing and iteration.
- Learn the fundamentals of Microsoft Fabric IQ, including how ontologies create a shared business vocabulary, the components that make up the Fabric IQ ecosystem, and how ontology modeling differs from traditional data modeling approaches.
By the end of this module, you'll be able to:
- Explain what Fabric IQ is and how ontologies define business vocabulary
- Describe the role of ontology items in creating entity types, properties, and relationships
- Distinguish between the roles of each Fabric IQ component: ontology items, data agents, Graph in Microsoft Fabric, and Power BI semantic models
- Compare ontology modeling's concept-driven approach with traditional use-case-driven data modeling
- Learn how to create ontologies in Fabric IQ by building manually or generating from Power BI semantic models, then bind ontology definitions to lakehouse tables and eventhouse streams.
By the end of this module, you'll be able to:
- Evaluate two approaches for creating an ontology in Fabric IQ
- Build an ontology manually by working with entity types, properties, keys, and relationships
- Generate an ontology from a Power BI semantic model
- Connect an ontology to data sources and preview the ontology
