330 Analytics Engineering Questions for dbt Core™ 1.11

This course contains the use of artificial intelligence.

Prepare for the dbt™ Analytics Engineering Certification Exam on dbt Core™ 1.11 by practicing decisions you would make in a dbt project. The 330 original questions focus on choosing an appropriate action, explaining a failure, and recognizing what a configuration does and does not guarantee.

A structured practice path

The course contains six question sets:

• Foundations, DAGs & Model Design: 50 questions on dependencies, materializations, reusable logic, commands, project configuration, and packages.
• Incremental Models, Python & Governance: 50 questions on incremental strategies, microbatch, snapshots, Python, access, contracts, versions, and constraints.
• Testing, SQL Semantics & Debugging: 50 questions on data and unit tests, SQL/Jinja behavior, failure thresholds, compiled code, and regression checks.
• Pipelines, Dependencies & State: 50 questions on DAG gates, clone, freshness, exposures, deferral, state selection, and retry.
• Two comprehensive practice exams: 65 questions each, with a suggested 120-minute limit per exam.

Each question includes the correct answer, feedback for every option, an overall explanation, and a focused review suggestion. Single-answer and select-two questions are clearly identified. Work through the topic sets first, then use the mixed sets to test decisions under different conditions rather than memorize repeated wording.

What the questions help you distinguish

Practice separates model shape from data quality, source event time from ingestion time, selected nodes from available dependencies, and compilation from execution. You will consider late-arriving records, empty incremental targets, sampled history, fixture limitations, adapter enforcement, stale state artifacts, and retained relations after a failed build.

The coverage follows all seven topic areas in the official 1.11 study guide. The mixed exams use a 65% practice target; this does not predict an official result or imply an official topic weighting. The real exam includes additional interactive question formats that these choice-based exercises do not reproduce.

This is a practice-question course, without video lessons or hosted warehouse labs. SQL knowledge and prior dbt project experience are expected. AI assisted question drafting, explanations, review, and the cover background; the material was checked against official documentation and available local SQL/Jinja execution. This does not represent an independent human expert review or a complete warehouse-based dbt validation.

This independently produced course is not affiliated with or endorsed by dbt Labs. It does not contain recalled exam questions, grant certification, or guarantee a passing score. Use the feedback to identify gaps and verify the relevant behavior in your own authorized development environment.

dbt, dbt Core, and dbt Labs are trademarks of dbt Labs, LLC.