The Who, What, and Why of Semantic Layers: The Layer That Decides Whether Your Numbers Can Be Trusted

Short summary

A semantic layer is an executable, machine-readable bridge between physical data tables and human questions, defining metrics, dimensions, and relationships once so every consumer gets the same governed answer. With AI agents now querying data directly, semantic layers have become critical: LLM accuracy on data questions jumps from ~40% to over 83% when grounded in a governed layer versus raw tables. The article surveys the full market including dbt, Cube, AtScale, Looker, and warehouse-native options from Snowflake and Databricks.

• •84% of data teams regularly encounter conflicting versions of the same metric
• •LLM accuracy on data questions jumps from ~40% to 83%+ when grounded in a semantic layer
• •Semantic layer definitions are executable, not just documentation — written once and consumed by all

Generated with AI, which can make mistakes.