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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You want to automatically deploy updates to your documentation site hosted on a cloud service whenever changes to your dbt project are committed to your main branch. Which of the following is essential for this setup?

A) Configuring dbt Cloud to trigger documentation deploys.
B) Enabling webhooks in your Git repository provider.
C) Implementing a CI/CD pipeline that includes dbt build steps.
D) Write a custom script to check for project changes and handle deployment.


2. Which of the following scenarios might warrant a git rebase instead of a standard git merge when integrating your changes into the main branch?

A) Your branch has diverged significantly from the main branch with unrelated changes.
B) You need to resolve complex merge conflicts that arise during a standard merge.
C) You only want to include a subset of your feature branch commits in the main branch.
D) You want to avoid a merge commit and keep a linear project history.


3. A performance-critical model depends on multiple complex transformations that would benefit from being pre-computed. Direct querying of this model should be as fast as possible. Which materialization is likely the best choice?

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


4. A teammate opens a pull request with numerous changes across many files. To help with the review process, you would suggest that they:

A) Resubmit the pull request as several smaller, more focused pull requests.
B) Provide a comprehensive summary of the intent and scope of the changes within the pull request description.
C) Use detailed commit messages to explain the rationale behind each set of related changes.
D) All of the above.


5. (Multiple Select)

A) Apply an incremental materialization strategy to subsequent models if appropriate.
B) Increase the query_comment timeout setting in your dbt_project. yml
C) Use CTEs or views in the source definition to pre-filter columns or apply initial transformations.
D) Introduce a source snapshot to create a point-in-time copy of the data.


Solutions:

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

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