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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. Your data warehouse is undergoing a migration to a different vendor (e.g., Snowflake to BigQuery). Which category of tools might play a critical role in ensuring a smooth transition of your dbt project?

A) SQL dialect translation tools
B) Cloud infrastructure management tools
C) Data virtualization tools
D) dbt adapters

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

3. The results of a dbt model contain values outside the expected range. You suspect an issue with Jinja templating. Where might this issue originate?

A) In the model's SQL, where you're using Jinja for calculations or dynamic logic.
B) Within a dbt_projectyml model or source configuration.
C) All of the above.
D) In a macro used by the model.

4. A downstream process relies on a critical model to be fully refreshed daily. How can you enforce this behavior using dbt_project.yml configuration?

A) Set the model's materialized property to incremental _ refresh-
B) Apply a post-hook that triggers a full refresh of the model.
C) Configure a schedule property within the models: section.
D) Update the model configuration to materialized: table and add a persist_docs: true property.

5. 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) models:
B) seeds:
C) snapshots:
D) vars:

Solutions: