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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

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

2. Your team establishes a policy for handling different levels of test failures (e.g., warnings vs. critical errors). How could you implement this policy effectively within your dbt workflows?

A) Use custom severity levels in your test definitions and a post-hook to manage actions accordingly.
B) Run dbt test multiple times with varying filters based on desired severity levels.
C) Rely on your data observability platform to differentiate and alert based on dbt test results.
D) Use dbt tags for classifying tests, then selectively execute them.

3. You're working on a dbt project in a development environment where compute resources are limited. You want to prototype a new model quickly without incurring high materialization overhead. Which materialization would be most suitable for this?

A) Incremental
B) Snapshot
C) Table
D) Ephemeral

4. You've created a complex lineage macro, and you want to include unit tests for the macro logic itself. How might you approach this?

A) Utilize dbt's built-in macro testing framework.
B) Include test cases for the macro within your model-level schema.yml files.
C) Currently, there is no standard way to directly unit test macros within a dbt project
D) Write a Jinja script that programmatically tests various input/output scenarios of your macro.

5. (Multiple Select)

A) Using separate dbt profiles for production and development environments
B) Scheduling less frequent jobs using dbt Cloud's built-in job scheduler
C) Implementing pre-hooks and post-hooks to perform tasks before and after dbt model execution.
D) Integrating dbt with your CI/CD tool and using job-specific triggers or filters.

Solutions: