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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You've created a pull request, and a discussion in the code review reveals issues with the approach you used in your feature branch. Rather than continuously updating the original branch, what's a strategy to address the feedback while keeping a clean pull request history?

A) Request that your collaborators edit the code directly within the pull request interface.
B) Add the changes as a new commit to your feature branch, explaining the revisions in the pull request comments.
C) Close the original pull request and create a new branch with the revised implementation.
D) Directly modify the commits on your existing feature branch using git rebase -i.

2. You discover that dbt models run significantly slower in your production environment than in development. What potential causes should you investigate?

A) Network latency impactingressing access to remote data sources.
B) Different database configurations or resource allocations (memory, CPU, etc.) between environments-
C) Inefficient use of snapshots or incremental models in your production dbt project_
D) Production data volume being significantly larger than development data.

3. You're working with a model that aggregates data across many countries. Which assumption about the data might be especially important to test for and handle in your model logic?

A) The presence of unexpected HTML tags within textual data fields.
B) Different regions may use varying currency exchange rates.
C) Time zones and daylight savings rules for timestamps could differ between data sources.
D) Encoding formats (UTF-8, etc.) may be inconsistent across source systems.

4. You want to trigger a dbt job immediately upon successful completion of an upstream ETL process. Which methods could achieve this?

A) Using the dbt build command to run all dependent models after a successful dbt run.
B) Configuring the ETL process to send a completion notification to your CIICD tool, triggering the dbt job.
C) Scheduling a dbt job with a very frequent interval (e.g., every 5 minutes) to poll for changes in a metadata table.
D) Using dbt Cloud's webhooks to create an endpoint that your ETL process can call.

5. You've defined several source models using .yml files within your models directory. When you run dbt compile, they don't appear in the DAG visualization. What's the MOST likely cause?

A) You haven't explicitly configured these sources in your dbt_project.yml file.
B) The source definitions require additional schema tests to be valid.
C) You haven't used the ref() function correctly within your source models.
D) The source tables are missing appropriate permissions in your database.

Solutions: