Master once. Activate everywhere.
Govern your semantic models across every platform. One mastered source. Governance in the middle.
Semantic models are created everywhere, mastered nowhere
Every platform governs its own semantics. Nobody governs all of them. The result: conflicting definitions, no single owner, and AI features that inherit the gaps. The problem is structural: semantics are created where data lives, but mastered nowhere.
How Semantic Model Mastering works
Four capabilities that take enterprises from fragmented semantic definitions to a single, governed source of truth — mastered at the point of consumption through data products.
Ingest from any platform
Create data products from Snowflake semantic views, Databricks metric views, Power BI, Looker, Cube, or YAML definitions from any platform. Built on the Open Semantic Interchange standard for cross-platform portability.
Govern through data products
Promote semantic models to data products with ownership assignment, approval workflows, version control, and quality standards. The data product becomes the mastered version, governed in one place.
Enrich beyond any single platform
Add glossary terms, curated descriptions, steward annotations, and relationship mappings. Richer context flows to downstream AI features, improving agent performance without changing how teams work.
Sync back to source systems
Materialize governed, enriched definitions back to Snowflake as semantic views and Databricks as metric views. AI features operate on mastered semantics without users ever entering Alation.
Master your semantic models across every platform
See how Alation governs semantic models across Snowflake, Databricks, Power BI, Looker, Cube, and more.
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