Models

We’ve spent years encoding business knowledge into Power BI semantic models. What a customer is, what revenue means. The problem is that knowledge is locked in DAX, invisible to AI agents. Fabric IQ introduces ontologies as the fix, a layer that captures meaning in a form machines can reason against. But generating an ontology from your existing semantic model inherits all its limitations. The real question is whether organisations will do the hard work of agreeing on definitions.

For years I thought dimensional models were about organizing data and making queries fast. That’s true, but it’s profoundly incomplete. Dimensional models describe how we store facts. They don’t describe what those facts mean. That gap shows up the moment someone asks a question your star schema wasn’t designed for. Ontologies solve a different problem: formal, machine-readable definitions of business concepts and their relationships. With Microsoft now shipping Fabric IQ, this conversation isn’t academic anymore.