Unified Data Model at Microsoft

Why a Unified Data Model is Critical: Lessons from Building Microsoft’s Semantic Layer

Anirudh,

Chris,

Nitin

Introduction Some years ago, we were wrestling with a persistent issue in our data stack. Every team had their own way of collecting and structuring data. What was a simple query for one team became a debugging nightmare for another. Discovering the right dataset felt like looking for a needle in a haystack, and standardizing definitions was almost impossible. These headaches slowed us down, hurt trust in our data, and left our AI models grappling with inconsistent input. When we started the effort to build a unified data model at Microsoft, we realized these problems weren’t just ours—they were universal. Thi...