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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. Security best practices dictate that data warehouse access should follow a "least privilege" principle. How would you implement this within dbt environments?

A) Leverage dbt's built-in grants mechanism to fine-tune object-level access within models.
B) Create separate data warehouse user accounts for development, staging, and production, each with minimal required permissions.
C) A combination of the above approaches.
D) Restrict access to sensitive data in development and staging environments using encryption or masking techniques.

2. You're loading fresh data from an external API. How would you implement dbt tests to ensure this feed is consistently providing up-to-date data?

A) Create a dbt model that directly queries the API in real-time as part of the dbt test run-
B) Test the maximum recorded timestamp in your model against the current timestamp, allowing for a small lag
C) Use a dbt source freshness test to define acceptable thresholds for the staleness of the source.
D) Write a custom test comparing the API response payload with previously captured data

3. A newly-hired analyst needs to update a downstream model that depends on a chain of intermediate models. To minimize the potential for disruption, how can modularity help them?

A) Snapshots ensure that historical data won't be impacted unintentionally.
B) By using macros, modifications are limited to a single location.
C) With clear dependencies, they can pinpoint which upstream models to test.
D) Incremental materializations will help verify that the changes are successful.

4. You discover that a heavily used model is taking significantly longer to materialize. After investigation, you determine that the complexity of the model's logic is a contributing factor. Which of the following actions is LEAST likely to help improve performance?

A) Consider applying an incremental materialization strategy if suitable.
B) Investigate potential optimizations in the underlying SQL code.
C) Break down the model into smaller, intermediate models using CTEs.
D) Change the materialization from a table to a view.

5. (Multiple Select)

A) Employ dbt snapshots to selectively run only models that depend on changed sources.
B) Configure separate dbt jobs with different schedules tailored to the model groups.
C) Use dbt tags to group models based on update frequency
D) Have all models run nightly but use where conditions within models to limit work when data is unchanged.

Solutions: