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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deployment and Orchestration | 15% | - CI/CD with dbt Cloud - Jobs and scheduling in dbt Cloud - Environments (dev, staging, prod) - Git version control integration |
| Topic 2: Testing and Documentation | 20% | - Custom data tests - dbt docs and DAG visualization - Documentation generation - Schema tests (unique, not_null, accepted_values, relationships) |
| Topic 3: Models | 25% | - Snapshots - Sources and references - Seeds - Writing and managing SQL models - Materializations (table, view, ephemeral, incremental) |
| Topic 4: dbt Fundamentals | 15% | - dbt workflow and best practices - dbt project structure - dbt Core vs dbt Cloud |
| Topic 5: Data Transformation Techniques | 25% | - Refactoring and incremental models - Macros and packages - Common table expressions and subqueries - Jinja templating |
dbt Labs dbt Analytics Engineering Certification Sample Questions:
(Multiple Select)
- A. Add -full-refresh flag to dbt run to ensure all models are rebuilt from scratch.
- B. IJse the -select flag with dbt run to execute models incrementally, starting with the most upstream dependency.
- C. Run dbt docs generate and dbt docs serve to inspect the lineage graph.
- D. Write custom macros to log intermediate data for each model.
Correct Answer: B,C 🗳️
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You're implementing singular tests (accepted values). After providing a list of valid values, you notice some strange behavior: the test is passing even with records that contain unexpected dat a. What's the most likely issue?
- A. A downstream process is overwriting the results after the model is built.
- B. The accepted_values test configuration has the wrong column specified.
- C. Your test case is accidentally permitting null values, which bypass the check.
- D. The model's data type isn't compatible with the accepted_values test.
Correct Answer: B,C,D 🗳️
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A teammate opens a pull request with numerous changes across many files. To help with the review process, you would suggest that they:
- A. Use detailed commit messages to explain the rationale behind each set of related changes.
- B. Provide a comprehensive summary of the intent and scope of the changes within the pull request description.
- C. All of the above.
- D. Resubmit the pull request as several smaller, more focused pull requests.
Correct Answer: B 🗳️
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Your dbt project contains sensitive dat
a. You need to load seed data (e.g., lookup tables) while ensuring it's not accidentally committed to version control. How can you best achieve this?
- A. Utilize environment variables to store seed data values.
- B. Create separate seed files and add them to your .gitignore or equivalent.
- C. Write the seed data into log files, excluding them from version control.
- D. Employ a secrets management tool and integrate it with your dbt deployment.
Correct Answer: B 🗳️
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A dbt deployment pipeline fails on the production environment, yet everything works as intended in development and staging. Which areas would you investigate when troubleshooting?
- A. Consider schema differences, if any between the production data warehouse and other environments.
- B. Ensure consistency of dependency versions across different environments-
- C. Check if all required permissions are granted to the dbt user on the production database.
- D. Verify the credentials and connection details between production and other environments in your profiles-yml.
Correct Answer: B 🗳️
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