dbt Labs dbt Analytics Engineering Certification : dbt-Analytics-Engineering

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

Question 1

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

Question 2

You need a materialization that automatically adapts to upstream schema changes while still preserving query performance. Which dbt materialization offers this kind of flexibility?

A. Ephemeral
B. Incremental
C. Snapshot
D. View

Question 3

You need to parameterize a dbt model that filters data based on a country code. Which approach offers the BEST combination of flexibility and security?

A. Build a dynamic query string entirely within a Jinja macro.
B. Pass the country code as a CLI argument when executing dbt run.
C. Use environment variables in conjunction with Jinja to substitute the country code.
D. Create a seed file mapping country codes to filter values and reference it in the model.

Question 4

You need to give read-only access to a specific dataset in your production data warehouse to a data analyst on your team. How might you approach this using dbt environments?

A. Use row-level security features in your data warehouse and dynamically filter data in models using environment variables.
B. Modify the data warehouse permissions directly to grant access to the required dataset.
C. Create a dedicated dbt target for the analyst and utilize grants within your models to control access.
D. A combination of the above, depending on the capabilities of your data warehouse.

Question 5

You suspect discrepancies in a critical model. To troubleshoot, you need to understand the order of model execution, but the DAG is complex. What would be the BEST strategy to get this information?

A. Run dbt docs generate and inspect the generated documentation.
B. Manually trace the dependencies in your model files.
C. Visually inspect the manifest.json file.
D. Use dbt Is -select

Solutions: