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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Leveraging dbt State | 5% | - State management - State-aware operations |
| Topic 2: Debugging and Error Resolution | 15% | - Debugging techniques - Identifying modeling errors - Resolving data quality issues |
| Topic 3: Developing dbt Models | 20% | - Model design and structure
|
| Topic 4: External Dependencies | 10% | - External sources integration - Using packages - Managing snapshots |
| Topic 5: Creating and Maintaining Documentation | 10% | - Descriptions and metadata - Documentation standards - Generating documentation |
| Topic 6: dbt Models Governance | 15% | - Version control integration - Naming conventions and standards - Project organization and structure |
| Topic 7: Implementing dbt Tests | 10% | - Custom tests - Built-in tests - Test configuration and execution |
| Topic 8: Managing Data Pipelines | 15% | - Pipeline orchestration - Deployment strategies - CI/CD integration |
1. (Multiple Select)
A) Implement custom metrics tracking the duration and resource usage of individual dbt models.
B) Using dbt Cloud's built-in job monitoring and notification features, if applicable.
C) Integrating dbt's logging with your existing monitoring and alerting platforms.
D) Require thorough code reviews with a focus on testability before deploying model changes to production.
2. You discover a vulnerability in a third-party lineage-enhancing dbt package you use. Where might you first look for information and potential fixes?
A) Only the authors of the dbt package would be able to address the vulnerability.
B) Centralized dbt documentation or a discussion forum.
C) The GitHub repository or documentation of the dbt package.
D) Directly in the manifest.json or packages.yml files within your project
3. A project stakeholder requests access to an intermediate stage of a dbt transformation pipeline to validate specific calculations.
You need to weigh this request carefully because:
A) All of the above-
B) Exposing intermediate results can lead to premature analysis based on incomplete data.
C) Granting access to intermediate data may confuse stakeholders who are not familiar with the full transformation process-
D) Raw data, development data, and production data often have different levels of data quality, completeness, and timeliness.
4. (Multiple Select)
A) Nesting multiple correlated subqueries within a single query_
B) Writing custom macros to encapsulate frequently used SQL logic.
C) Using SELECT * to include all columns dynamically
D) Leveraging window functions to calculate values across rows or groups.
5. You need to grant readonly access to a new stakeholder on a specific dbt model's output. What factors should influence your approach?
A) Whether you wish to provide direct table access or a view-based interface.
B) If this is a one-time need, or something requiring scalable permission management.
C) The database technology and its permissions model.
D) The default materialized setting defined for models in your dbt_project_yml file.
Solutions:
| Question # 1 Answer: A,B,C | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: A,C | Question # 5 Answer: A,B,C |
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