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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You define a source table and include an override:YAML

A) The overrides property is not valid for tables within your dbt_project.yml.
B) You need to create a macro named 'my_project' that contains the specific overriding logic.
C) The value 'my_project' is not a recognized keyword by dbt.
D) The overrides property needs to be defined at the source level, not the table level.

2. You're merging changes from a feature branch into your main branch. Which of the following Git commands or strategies help keep a clean and easy-to-follow project history?

A) Utilizing git rebase main before merging to linearize the history.
B) Employing git squash merge for condensing feature branch commits.
C) All of the above can be valid strategies, each with different trade-offs.
D) Using git merge to create a merge commit.

3. You're setting up baseline comparisons with historical dat
a. Which factors are crucial to consider when selecting or generating the baseline dataset?

A) The baseline should cover a representative time range relevant to your analysis.
B) The data volume in the baseline should be large enough to identify statistical patterns.
C) The baseline needs to align in structure (schemas) with the dbt models being tested.
D) If using data, the baseline might need sanitization to remove PII-

4. Your dbt project pulls data from a SaaS application using a third-party adapter. You observe performance issues. Where might you start optimizing?

A) Review the source definitions to see if unnecessary data is being selected.
B) Investigate the third-party adapter's settings or documentation for potential bottlenecks.
C) Configure the source as an incremental materialization within your project file.
D) Check your dbt_project.yml for project-level performance settings.

5. You're expanding your dbt deployment to support a new regional team based in a different geographic location from your main development team. They'll access the same production data in your centralized data warehouse. Which factors need careful consideration?

A) Controlling dbt access based on team membership and geographic location to align with security policies.
B) Data residency regulations that might restrict the flow or storage of data between geographic regions.
C) Potential network latency affecting performance of dbt runs for the geographically separate team.
D) All of the above.

Solutions: