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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Debugging and Error Resolution15%- Identifying modeling errors
- Resolving data quality issues
- Debugging techniques
Topic 2: External Dependencies10%- External sources integration
- Using packages
- Managing snapshots
Topic 3: dbt Models Governance15%- Version control integration
- Project organization and structure
- Naming conventions and standards
Topic 4: Leveraging dbt State5%- State management
- State-aware operations
Topic 5: Creating and Maintaining Documentation10%- Documentation standards
- Descriptions and metadata
- Generating documentation
Topic 6: Managing Data Pipelines15%- Deployment strategies
- Pipeline orchestration
- CI/CD integration
Topic 7: Implementing dbt Tests10%- Custom tests
- Test configuration and execution
- Built-in tests
Topic 8: Developing dbt Models20%- Model optimization
  • 1. Model contracts
  • 2. Performance tuning
- Model design and structure
  • 1. Materialization types
  • 2. Incremental models
  • 3. Ref and source functions

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You're working on a dbt project in a development environment where compute resources are limited. You want to prototype a new model quickly without incurring high materialization overhead. Which materialization would be most suitable for this?

A) Incremental
B) Table
C) Ephemeral
D) Snapshot


2. During development, you frequently used temporary print statements for debugging. Which of the following is the best practice before opening a pull request?

A) Remove the print statements entirely from your commits-
B) Consolidate the print statements into a separate debugging function that can be toggled on and off
C) Comment out the print statements but leave them in the code.
D) Leave the print statements for future reference, in case similar debugging is needed-


3. Dependency Break

A) Adding schema tests to the source table to catch structural changes early on.
B) All of the above.
C) Setting up alerts or notifications if dbt runs fail unexpectedly in a production environment.
D) Using the dbt deps command to visualize dependencies and anticipate potential impacts.


4. (Multiple Select)

A) Models addressing a domain-specific use case (e.g., subscription analytics).
B) Macros for fiscal period calculations or string manipulations.
C) A custom adapter to connect to a niche data source.
D) Snapshots that track the state of your sources on a schedule.


5. When merging code on a remote repository hosting platform (like GitHub), you notice options like "squash and merge" and "rebase and merge." Which factors would influence your choice between these options?

A) The size and complexity of the changes within the pull request.
B) All of the above.
C) Whether you want to preserve the feature branch commit history in detail.
D) Your team's established conventions and preferences for maintaining the project history.


Solutions:

Question # 1
Answer: C
Question # 2
Answer: A
Question # 3
Answer: B
Question # 4
Answer: A,B
Question # 5
Answer: B

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