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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You've defined development, staging, and production targets in your dbt project. You want to prevent accidental execution of destructive model materialization strategies (like drop or truncate) on the production target. How could you achieve this?

A) Write a custom macro that only executes such operations on non-production targets.
B) Rely purely on thorough code reviews to prevent execution of these commands in production.
C) Create a separate profiles.yml file for production that disables dangerous materialization strategies.
D) Implement a CI/CD process that includes checks to prevent specific dbt commands from running in the production environment

2. You need a very niche data transformation that no existing packages address. When should you consider building your own dbt package?

A) Whenever you need to encapsulate custom SQL logic for reuse across models.
B) Only after you have extensively searched for potential alternative solutions.
C) If the transformation logic is complex and likely to be valuable to others in the dbt community.
D) When strict versioning and control of the functionality are critical for your project

3. You're setting up a new dbt project and want to customize the naming of compiled objects in the data warehouse. Which section of the dbt_project.yml file is the most relevant?

A) seeds:
B) models:
C) vars:
D) snapshots:

4. You introduce a minor formatting change to a large SQL model. Afterwards, the results change unexpectedly. Which dbt-related issue might explain this, even if the SQL itself appears correct?

A) There's a version mismatch between the dbt library used during development and in production.
B) An upstream data issue only surfaces due to the formatting change making that part of the query execute differently.
C) You've used a reserved keyword as a column alias without properly quoting it.
D) A subtle indentation change in a CTE accidentally modifies the execution order within the query.

5. You've included some custom visualizations within your dbt project documentation (e.g., network graphs) but notice they don't render correctly when the site is generated. What might be the cause?

A) Custom visualizations usually require additional JavaScript libraries to be included.
B) Your visualization definitions haven't been configured correctly in the project YAML files
C) The dbt docs generate command has a strict limit on the file size of visualizations it can process-
D) Custom visualizations are not directly supported by dbt's built-in documentation.

Solutions: