Mastering data quality with dbt

Build a durable data quality practice in dbt—beyond “a few tests.” This course focuses on choosing the right type of test for the job, keeping tests maintainable as a project grows, and adding quality gates (like CI) that prevent bad changes from reaching production. You’ll leave with a practical, reusable approach to testing strategy and enforcement.

After this course, you will be able to:

Identify which quality technique fits the problem (schema tests, data tests, unit tests, and CI checks)

Implement a maintainable testing strategy (what to test, where to place tests, and how to avoid brittle patterns)

Understand CI workflows to catch quality regressions before merge and deploy