Testing Strategies That Actually Catch Bugs in dbt

Most dbt projects start with a handful of not_null and unique tests, and then stop there. Those tests are valuable, but they only scratch the surface of what can go wrong in a pipeline.

The most impactful tests encode business logic. Does revenue always reconcile across two independent sources? Are there orphaned records after a join? Relationship tests, accepted-range checks, and custom singular tests catch the subtle issues that generic schema tests miss.

Equally important is deciding when a test should warn versus error. A failing test that halts the entire build trains people to ignore failures. Severity thresholds let you distinguish between 'this needs attention soon' and 'stop everything now.'

Pair your tests with freshness checks and source assertions, and you build a safety net that gives stakeholders genuine confidence in the numbers they see.