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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. Your baseline comparison tests start failing intermittently. Data distributions change slightly from day to day, sometimes triggering the thresholds. Which strategy could make your tests more robust?

A) Rewriting your SQL to compare averages or medians instead of exact value counts-
B) Scheduling the tests to run less frequently (e.g., weekly rather than daily).
C) Removing the baseline comparison tests entirely, as they provide unreliable signals.
D) Introducing configurable tolerances into your test definitions.

2. (Multiple Select)

A) Require thorough code reviews with a focus on testability before deploying model changes to production.
B) Implement custom metrics tracking the duration and resource usage of individual dbt models.
C) Using dbt Cloud's built-in job monitoring and notification features, if applicable.
D) Integrating dbt's logging with your existing monitoring and alerting platforms.

3. (Multiple Select)

A) The cost-efficiency of the development environment solution.
B) The overall size and complexity of your dbt project
C) The need for feature parity (functions, syntax) with the production warehouse.
D) The technology used for your production data warehouse.

4. External Dependency

A) Work with stakeholders to understand if the external change is intentional and adjust the business logic if needed.
B) Introduce a temporary staging model to transform the data into a compatible structure for your existing models.
C) All of the above.
D) Implement schema tests for the affected models to catch similar breakages immediately in the future.

5. (Multiple Select)

A) Introduce a source snapshot to create a point-in-time copy of the data.
B) Apply an incremental materialization strategy to subsequent models if appropriate.
C) Increase the query_comment timeout setting in your dbt_project. yml
D) Use CTEs or views in the source definition to pre-filter columns or apply initial transformations.

Solutions: