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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. Performance Bottleneck

A) Add -full-refresh to dbt run on the model to ensure downstream models don't cause errors.
B) Run EXPLAIN or equivalent on the compiled query to pinpoint the most expensive operations.
C) Introduce CTEs to pre-calculate aggregated data or common subexpressions, especially if reused repeatedly.
D) Implement database-level indexes on columns involved in the joins, if appropriate.

2. A pull request includes changes to both dbt models and configuration files in your dbt_project.yml file. During the merge, conflicts arise in the configuration file. How would you approach resolving these conflicts?

A) Ask the author of the pull request to rebase their changes and resolve the configuration conflict in their branch.
B) Give priority to the model changes and manually edit the configuration file after.
C) Request a separate, smaller pull request dedicated to the configuration changes to isolate the conflict.
D) Utilize Git's merge conflict markers to carefully combine changes in the configuration file.

3. Your team follows a convention where commit messages include a relevant issue tracker reference (e.g., JIRA- 123). You've been working on multiple features and fixes. Which of the following best promotes clean commits?

A) Commit all your changes at once with a generic message like "Project updates."
B) Break down your changes into smaller, atomic commits, each referencing the issue it addresses.
C) Don't worry about commit messages, as the pull request title and description are more important.
D) Include all relevant issue references in a single commit message when you're ready to create a pull request.

4. Regular test runs reveal inconsistent and intermittent test failures, despite no obvious changes to models or source dat a. What debugging strategies might you use?

A) Temporarily switch to a more consistent testing environment.
B) Use dbfs logging feature to add detailed output to the test execution.
C) Consider if external dependencies used within dbt tests are themselves unstable.
D) Examine data warehouse performance metrics for resource constraints during test runs.

5. A common dimension table is used in 80% of your models. What might be a side effect of frequently changing the structure of this dimension?

A) It would cause errors in models that are not directly dependent on this dimension.
B) Compile times would significantly increase across the project.
C) The dbt docs output would become unmanageable.
D) You might need to update a large number of downstream models.

Solutions: