What it is
Fabric IQ is the semantic ground beneath Fabric AI. It defines how your business actually works — the entities, the relationships, the metrics, the policies — and exposes that definition to agents so they can reason correctly. Without an ontology, agents treat "revenue" the way an LLM does. With one, they treat it the way your CFO does.
Ontology
An ontology in Fabric IQ is a curated definition of your business domain: entities (Account, Order, Product), relationships (Account has-many Orders), attributes, and KPIs. It can reference semantic models, lakehouses, and KQL databases as its data backing, so the ontology stays grounded in real data rather than abstracted away.
Fabric Graph
Fabric Graph is the graph database that makes the ontology queryable. It stores entity instances and relationships, supports graph traversal queries (Cypher-style), and integrates with lineage, security, and Data Agent retrieval.
Plan
A Plan is a Fabric IQ item that defines goals, constraints, and decision logic — used by Operations Agents to reason about what action to take. Think of it as the "if/then" layer expressed at a business-policy level rather than at the code level.
Agents on top
Once the ontology, graph, and plans are in place, agents become small and powerful:
- Data Agents ground in the ontology to answer questions in business terms.
- Operations Agents apply plans against live data to take actions.
Adoption path
- Pick one business domain. Finance, supply chain, or customer ops. Not all three.
- Map the entities. 10–25 entities is plenty for v1. Document each in the ontology.
- Wire to the semantic model. Each entity binds to tables, measures, or KQL queries.
- Build one Data Agent. Validate ontology fidelity through real questions.
- Add a Plan + Operations Agent. One high-value automation. Recommendation-mode first.
- Iterate the ontology. Real usage exposes gaps. The ontology is a living artifact.