Online Access Free dbtLabs.dbt-Analytics-Engineering.v2026-03-04.q170 Practice Test (Page 25)

dbt-Analytics-Engineering Exam Question 116

Your company wants to standardize pull request templates. Which information would be beneficial to include in such a template?

A.Checkboxes for confirming that tests have been run and documentation has been updated if necessary.

B.A section to link to relevant design documents or specifications.

C.Specific instructions for the reviewer, if certain aspects need special attention.

D.All of the above.

dbt-Analytics-Engineering Exam Question 117

You're experimenting with new transformations. You want to iterate on a model without affecting data in the production warehouse. Which dbt command should you use along with appropriate flags?

A.dbt seed with -select to load data into production.

B.dbt test with -defer to temporarily bypass upstream dependencies.

C.dbt run with -target to specify a development environment.

D.dbt compile to ensure changes are valid without executing models.

dbt-Analytics-Engineering Exam Question 118

(Multiple Select)

A.Configuring tests to run only on models that have changed or have upstream changes.

B.Running dbt tests in parallel with dbt model builds whenever possible-

C.Scheduling less critical tests to run during off-peak hours.

D.Designing tests, where feasible, to examine subsets of data rather than full tables.

dbt-Analytics-Engineering Exam Question 119

You have a dbt macro that generates a list of models to execute dynamically. Which dbt command should you use in conjunction with this macro to actually run those models?

A.dbt parse to pre-compile the project graph, allowing model selection by reference.

B.dbt Is to retrieve project metadata and feed it into your custom execution logic.

C.dbt debug to step through model execution while using the macro's output

D.dbt build to create a task graph, extracting model nodes, and running them as needed.

dbt-Analytics-Engineering Exam Question 120

You need to test for consistency between a raw source table and its corresponding dbt model after transformation. This requires comparing many columns for null counts and matching value distributions. Which approach would be most efficient?

A.Manually writing SQL queries to separately calculate and compare these metrics.

B.Using dbt's built-in source freshness tests for a high-level check.

C.Creating a custom dbt test that leverages statistical comparison techniques.

D.Relying entirely on generic not_null and unique tests.

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dbt-Analytics-Engineering Exam Question 116

dbt-Analytics-Engineering Exam Question 117

dbt-Analytics-Engineering Exam Question 118

dbt-Analytics-Engineering Exam Question 119

dbt-Analytics-Engineering Exam Question 120

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