dbt Analytics Engineering study guide
dbt Analytics Engineering · Work through your exam, one topic at a time.
This page is an independent study guide for the dbt Analytics Engineering certification. It is written for analytics engineers, BI developers, and data practitioners who build, test, document, and deploy transformation projects with dbt, and who want a structured way to prepare for a certification exam in that space. The material is organised around four domains that carry equal weight: data modelling and transformation with dbt; sources, tests, and data quality; documentation, lineage, and governance; and deployment, orchestration, and project configuration. Each domain is treated as a working skill area rather than a list of trivia, because certification-style questions tend to present a project scenario and ask which configuration, test, or command produces the intended behaviour. The dbt Analytics Engineering study guide has 4 sections and about 1,802 words.
01Data Modeling and Transformation with dbt
This domain tests your ability to structure transformations, choose materializations, and express dependencies correctly. The exam favors practical decisions: which layer a model belongs in, when an incremental model is safe, and how configuration precedence changes the compiled result.
464 words, about 2 min02Sources, Tests, and Data Quality
This domain examines how you declare raw data, measure freshness, and encode assumptions as tests. The exam focuses on what dbt actually executes: freshness queries against sources and test queries that return failing rows.
471 words, about 2 min03Documentation, Lineage, and Governance
This domain covers how dbt makes a project understandable and controlled: descriptions, generated documentation, lineage, exposures, ownership, groups, access, contracts, and versions. The exam tests whether you know which metadata is descriptive and which metadata actually enforces behavior.
446 words, about 2 min04Deployment, Orchestration, and Project Configuration
This domain tests how a dbt project is configured, promoted across environments, and run reliably. The exam emphasizes configuration files, environment targets, artifact-based state, and the difference between running models and running a full build.
421 words, about 2 min