CodersSecret

Course guide

dbt Data Quality and Testing Course

Learn data quality with dbt-style tests, freshness checks, relationship tests, contracts, documentation, and data incident debugging.

Data quality is not a cleanup project. It is an engineering workflow. This course teaches not_null, unique, accepted values, relationship tests, freshness checks, contracts, and incident debugging for trusted analytics.

Learning path

Continue from concept to implementation

These course modules place this topic in context, connect it to adjacent decisions, and provide the practical next step.

Module 6

Marts: Facts and Dimensions

Create the business-facing layer: facts, dimensions, and star schemas.

110 minutes | 3 learning objectives

Module 7

Testing and Data Quality

Use tests to catch broken assumptions before users lose trust.

110 minutes | 3 learning objectives

Module 8

Freshness, Contracts, and Documentation

Make data understandable, current, and safe to change.

95 minutes | 3 learning objectives

Practical outcomes

What the recommended module teaches

  • Use not_null, unique, relationships, and accepted_values tests
  • Write testable assumptions in model YAML
  • Connect data quality to user trust