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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: External Dependencies | 10% | - Managing snapshots - Using packages - External sources integration |
| Topic 2: Developing dbt Models | 20% | - Model optimization
|
| Topic 3: Managing Data Pipelines | 15% | - CI/CD integration - Deployment strategies - Pipeline orchestration |
| Topic 4: Leveraging dbt State | 5% | - State management - State-aware operations |
| Topic 5: Creating and Maintaining Documentation | 10% | - Documentation standards - Generating documentation - Descriptions and metadata |
| Topic 6: Implementing dbt Tests | 10% | - Built-in tests - Custom tests - Test configuration and execution |
| Topic 7: Debugging and Error Resolution | 15% | - Identifying modeling errors - Resolving data quality issues - Debugging techniques |
| Topic 8: dbt Models Governance | 15% | - Naming conventions and standards - Project organization and structure - Version control integration |
dbt Labs dbt Analytics Engineering Certification Sample Questions:
A new feature you're developing requires significant changes across multiple models in your dbt project. Which branching strategy would be the most suitable and why?
- A. Avoid using branches altogether, as they can introduce unnecessary complexity into a dbt workflow
- B. Work directly on the main branch, as it ensures your changes are always up-to-date.
- C. Create separate branches for each model you'll be modifying to minimize conflicts.
- D. Create a feature branch for the new development to isolate your work.
Correct Answer: D 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
You create tests to validate counts and timestamps against a baseline dataset. The tests fail unexpectedly. What might be possible root causes?
- A. Your tests are too strict and need more generous tolerances.
- B. There are differences in data types or time zone handling between the model and baseline.
- C. Your upstream ETL process has a logic error, leading to incorrect data.
- D. The baseline dataset itself has become corrupted
Correct Answer: A,B,C,D 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
You're using dbt Cloud and want to tighten control over when production deployments can occur. What dbt Cloud feature, in conjunction with your CI/CD configuration, would allow you to enforce this?
- A. dbt Cloud's built-in source freshness checks.
- B. Deployment jobs and schedules.
- C. Webhooks for triggering jobs by external events.
- D. Environment variables for sensitive credentials.
Correct Answer: B 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
You're getting inconsistent errors when adding new models in your dbt_project.yml. You suspect typos or indentation issues. How can you proactively improve this situation?
- A. All of the above.
- B. Use a code editor or IDE with YAML-specific linting and auto-formatting support.
- C. Write tests covering various aspects of dbt_project.yml to proactively catch errors.
- D. Set up a pre-commit hook that runs a YAML validation script before committing changes.
Correct Answer: A 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
(Multiple Select)
- A. Tools specializing in schema change detection.
- B. Data integration testing frameworks (e.g., Great Expectations)
- C. Anomaly detection platforms.
- D. Continuous Integration (Cl) tools.
Correct Answer: A,B,C 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
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