Introduction to Semantic Modeling

Across analytics and AI platforms, semantic models provide shared definitions for metrics, dimensions, and relationships. These definitions can be used across tools and workflows, reducing duplication and ensuring consistency. In Hex, semantic modeling brings these same benefits directly into your workspace, ensuring that both human and AI driven analyses use the same consistent, trusted definitions.

To use semantic models in Hex, you can either author them directly using the Modeling Workbench, or connect existing models from external platforms using Semantic Model Sync. This gives you flexibility to either author models natively in Hex or bring in definitions from tools like Cube, dbt MetricFlow, or Snowflake Semantic Views.