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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. Which of the following scenarios would likely require you to use the -no-compile flag with the dbt docs generate command?

A) You've made syntax errors in your model definitions and want to prevent documentation errors due to compilation failures.
B) Adding a new model and its corresponding description in your project.
C) Updating existing column descriptions to reflect recent upstream changes.
D) Running the documentation generation process in a production setting where compilation could introduce risks.

2. You're merging changes from a feature branch into your main branch. Which of the following Git commands or strategies help keep a clean and easy-to-follow project history?

A) Employing git squash merge for condensing feature branch commits.
B) All of the above can be valid strategies, each with different trade-offs.
C) Utilizing git rebase main before merging to linearize the history.
D) Using git merge to create a merge commit.

3. After implementing thorough dbt tests, you confidently deploy changes. Yet, downstream Bl dashboards break, and stakeholders complain about inaccurate dat a. What could have gone wrong?

A) There are logic errors in your dbt models that the tests didn't catch.
B) Your tests were correct, but a bug in dbt prevented them from running successfully.
C) Critical assumptions were made about the data in the Bl layer, independent of dbt models.
D) The tests you wrote were too strict, causing false positives.

4. You define several sources. However, some are frequently updated, while others rarely change. How can you optimize your dbt run command to account for this difference?

A) Group sources based on update frequency and create separate dbt run commands for each group.
B) Include the -exclude flag along with less-frequently updated source names.
C) Employ the defer option if downstream models permit and ensure freshness checks are adjusted.
D) Set up dbt schedules within your dbt_project.yml with different intervals for each group.

5. dbt Model Snippet:SQL

A) The GROUP BY month clause leading to duplicate rows.
B) Incorrect Jinja usage within a macro used for templating.
C) The SUM(order_amount) aggregation logic.
D) The source() function retrieving data from the incorrect schema.

Solutions: