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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You've meticulously added descriptions and tests to your dbt models. However, after running dbt docs generate, the tests don't appear in the generated documentation. Which of the following reasons are most likely?

A) Your tests have incorrect syntax, and dbt is silently skipping them during documentation generation.
B) There is a bug in the version of dbt you're using that specifically affects test rendering in documentation.
C) The dbt_project.yml file may not have the appropriate settings for including tests in the documentation.
D) You are using a custom schema test macro that isnt configured to be included in the documentation.

2. (Multiple Select)

A) Designing tests, where feasible, to examine subsets of data rather than full tables.
B) Scheduling less critical tests to run during off-peak hours.
C) Configuring tests to run only on models that have changed or have upstream changes.
D) Running dbt tests in parallel with dbt model builds whenever possible-

3. A package you depend on has released a major update with breaking changes. How might you approach the migration?

A) Review the release notes and the migration guide provided by the package maintainers.
B) Pin the package to the older version in your packages.yml file and plan a controlled migration.
C) Update your packages.yml to point to the new version and immediately refactor all your dependent models.
D) Fork the package and maintain your own custom version indefinitely.

4. "We can just load everything into our warehouse and let dbt handle it." How would you respond to this approach suggested by a stakeholder?

A) All of the above.
B) Introducing sensitive data sources requires careful consideration and might be better handled outside the warehouse.
C) dbt models might become unnecessarily complex due to unfiltered data.
D) It could become expensive due to storage and compute costs, especially with large, raw datasets.

5. (Multiple Select)

A) Integrate a specialized data lineage tool that tracks dependencies down to the database level..
B) Leverage your data warehouse's built-in auditing or change tracking features, if available.
C) Configure dbt to log all executed SQL statements with sufficient metadata for auditing.
D) Enable version control on your dbt_project.yml file and related configuration.

Solutions: