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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You want to display the runtime metrics (e.g., execution time) of each model directly on the DAG node. Which challenges might you face when implementing this?

A) Adding too much detailed information directly to the DAG could lead to visual clutter and make it overwhelming.
B) dbt documentation is primarily static; it might not be able to render dynamic metrics that change with each execution.
C) Retrieving runtime metrics for each historical run might not be natively supported by dbt
D) All of the above

2. A project stakeholder requests access to an intermediate stage of a dbt transformation pipeline to validate specific calculations.
You need to weigh this request carefully because:

A) All of the above-
B) Exposing intermediate results can lead to premature analysis based on incomplete data.
C) Granting access to intermediate data may confuse stakeholders who are not familiar with the full transformation process-
D) Raw data, development data, and production data often have different levels of data quality, completeness, and timeliness.

3. A new feature you're developing requires significant changes across multiple models in your dbt project. Which branching strategy would be the most suitable and why?

A) Create a feature branch for the new development to isolate your work.
B) Work directly on the main branch, as it ensures your changes are always up-to-date.
C) Create separate branches for each model you'll be modifying to minimize conflicts.
D) Avoid using branches altogether, as they can introduce unnecessary complexity into a dbt workflow

4. You're working with ephemeral models in your dbt project. Which scenarios could cause an ephemeral model to fail?

A) A syntax error in the model's SQL code.
B) Data quality tests defined within the model are not met.
C) An upstream source table is temporarily inaccessible.
D) A downstream dependency of the ephemeral model fails.

5. (Multiple Select)

A) Implementing more rigorous access controls and auditing procedures.
B) Scheduling models to run outside normal business hours to reduce resource contention.
C) Using credentials with appropriate permissions (likely read-only) to access production data sources.
D) Potentially running on a different data warehouse or with different database settings.

Solutions: