Testing
Elementary is an open-source dbt package that adds data observability to your existing dbt project. It turns dbt models into monitored data assets: tracking volume changes, schema changes, freshness, and statistical anomalies in column distributions — without changing your existing dbt tests. Where dbt's built-in tests (not_
Testing
dbt snapshots implement Slowly Changing Dimensions (SCD Type 2) — tracking how a record changes over time by keeping the full history. A bug in snapshot configuration silently corrupts your history, making past-dated reports wrong. Testing snapshots requires validating that history is captured correctly, records are updated (not duplicated), and
Testing
Recce is a dbt change review tool that answers one question: what did this PR actually change in the data? When you modify a dbt model, your CI runs dbt tests and they pass — but that only tells you the data is valid, not whether it changed. Recce builds the
Testing
dbt ships with four built-in tests (not_null, unique, accepted_values, relationships) that cover the basics. For richer assertions—value ranges, regex patterns, statistical checks—add the dbt-expectations package. When neither covers your case, write a custom generic test. This guide covers all three layers plus how to