Online Access Free dbtLabs.dbt-Analytics-Engineering.v2026-03-04.q170 Practice Test (Page 22)

dbt-Analytics-Engineering Exam Question 101

You introduce performance optimizations to a subset of models. You need to benchmark both old and new versions in an isolated environment before deployment. How might you structure your dbt commands for this comparison?

A.Use feature branches and switch between them with different dbt profiles for old and new code.

B.Utilize dbt seed to populate separate datasets representing the old and new model outputs for side-by-side analysis.

C.Add dbt hooks to temporarily archive the original output tables before overwriting them during benchmark runs.

D.Within a model, conditionally write to different schemas based on an environment variable, preserving both versions.

dbt-Analytics-Engineering Exam Question 102

You've made several commits to your feature branch. Before merging into the main branch, you want to consolidate the changes into a single, clear commit. What Git technique would help achieve this?

A.git cherry-pick specific commits from your branch and reapply them.

B.Run git rebase main followed by git commit -amend.

C.Use git rebase -i (interactive rebase) to squash commits together.

D.Manually copy your files into a new branch, commit, and issue a pull request.

dbt-Analytics-Engineering Exam Question 103

You have a complex dbt model that is essential for production reporting. To minimize the risk of breaking this model during development, what strategy might you employ?

A.Configure production jobs to use a pinned version of the dbt model.

B.Write extensive tests targeting this model in your production environment

C.Create a duplicate model in production and only sync changes once they're fully tested-

D.Rely on your data warehouse's native rollback functionality to reverse changes if needed.

dbt-Analytics-Engineering Exam Question 104

Your team decides to use separate databases within the data warehouse for development, staging, and production. Which are the potential benefits of this approach?

A.Increased isolation of changes between environments, reducing the risk of unintended consequences in production.

B.The ability to fine-tune database configurations and permissions specifically for each environment's purpose.

C.Simplified testing and deployment processes due to clear separation of environments.

D.All of the above.

dbt-Analytics-Engineering Exam Question 105

The results of a dbt model contain values outside the expected range. You suspect an issue with Jinja templating. Where might this issue originate?

A.Within a dbt_projectyml model or source configuration.

B.In a macro used by the model.

C.In the model's SQL, where you're using Jinja for calculations or dynamic logic.