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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You discover a downstream model, dim products, references an outdated raw dataset, raw_product_archive, intended for historical analysis and not active products. What's the most appropriate corrective action?

A) Leave it as-is since it's not actively causing any errors currently.
B) Delete the raw_product_archive source, so it can't be used accidentally.
C) Update the dim_products model to reference the active product dataset.
D) Add a schema test to dim_products to catch potential errors.

2. (Multiple Select)

A) Defining generic tests that apply to multiple data sources.
B) Populating a lookup table with country codes.
C) Loading configuration data for production environments that differs from development settings.
D) Inserting large volumes of historical transactional data for backfilling purposes.

3. A pull request targeting your main branch has been approved in code review but requires changes after automated tests fail. To address this, you should:

A) Disable the automated tests temporarily, merge, and re-enable tests later.
B) Directly modify the branch by pushing commits to fix the tests.
C) Ask the branch author to add new commits fixing the issues. Then merge when tests pass.
D) Merge the pull request despite the failing tests, resolving the issues in a subsequent fix.

4. A dbt deployment pipeline fails on the production environment, yet everything works as intended in development and staging. Which areas would you investigate when troubleshooting?

A) Verify the credentials and connection details between production and other environments in your profiles-yml.
B) Ensure consistency of dependency versions across different environments-
C) Consider schema differences, if any between the production data warehouse and other environments.
D) Check if all required permissions are granted to the dbt user on the production database.

5. (Multiple Select)

A) Inserting rows for a generic date dimension table.
B) Loading data to fact tables as part of the regular ETL process.
C) Adding test records to validate a new custom data test.
D) Populating a staging environment with representative data for testing.

Solutions: