validating-semantic-model

To validate a Fabric semantic model against dbt sources, parse dbt_project.yml, schema YAMLs, and TMDL files to confirm alignment, referential integrity, and naming conventions before deployment.

TMDL semantic model validation detects structural issues like missing required files, relationship errors like orphan keys and circular paths, and measure problems including missing documentation and source model drift.

Dbt to TMDL referential integrity validation parses dbt schema YAMLs and TMDL files to ensure all referenced tables exist, cross-filtering is proper, and data types remain consistent across models.

Yes, you can check naming conventions and structural rules in TMDL files by validating required files, enforcing naming and type rules, and verifying that all referenced tables exist within the Fabric project.

Yes, you need a dbt project containing dbt_project.yml and schema YAMLs alongside your TMDL files to verify consistency and alignment with Fabric best practices and dbt data definitions.

The best way to surface drift between dbt models and Fabric semantic models is running a validator that parses TMDL files and dbt sources to generate a structured report of misconfigurations and remediation steps.