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| Section | Weight | Objectives |
|---|
| Topic 1: Debugging and Error Resolution | 15% | - Resolving data quality issues - Debugging techniques - Identifying modeling errors
|
| Topic 2: dbt Models Governance | 15% | - Version control integration - Naming conventions and standards - Project organization and structure
|
| Topic 3: Managing Data Pipelines | 15% | - Deployment strategies - Pipeline orchestration - CI/CD integration
|
| Topic 4: Developing dbt Models | 20% | - Model optimization
- 1. Model contracts
- 2. Performance tuning
- Model design and structure
- 1. Ref and source functions
- 2. Incremental models
- 3. Materialization types
|
| Topic 5: External Dependencies | 10% | - Managing snapshots - Using packages - External sources integration
|
| Topic 6: Implementing dbt Tests | 10% | - Test configuration and execution - Custom tests - Built-in tests
|
| Topic 7: Leveraging dbt State | 5% | - State management - State-aware operations
|
| Topic 8: Creating and Maintaining Documentation | 10% | - Documentation standards - Descriptions and metadata - Generating documentation
|
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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q253-Q258):
NEW QUESTION # 253
A team member suggests building a dbt package for a set of reusable transformations your team frequently uses. When is this MOST likely a good idea?
- A. The transformations are complex and involve domain-specific logic that might be beneficial to others.
- B. The transformations are relatively simple and could be written as macros.
- C. The transformations are project-specific but used across multiple models.
- D. You need to limit access to these transformations to a specific team within your organization.
Answer: A
Explanation:
Sharing common, complex logic is a key reason for creating packages. Simple logic is better as macros. Project-specificity favors macros or CTEs. Packages arent ideal for access control.
NEW QUESTION # 254
While reviewing a dbt project, you notice a pattern where ref() calls are chained together:
Model A references Model B, which in turn references Model C.
What's a potential downside of this pattern?
- A. Decreased performance due to unnecessary materializations.
- B. Test results might become less reliable.
- C. Version control conflicts become more likely.
- D. Model dependencies become harder to track and understand.
Answer: D
Explanation:
While chaining ref() calls works technically, it can quickly make dependency tracking overly complex, especially in larger projects.
NEW QUESTION # 255
(Multiple Select)
- A. You want to test different loading strategies for a large source table.
- B. The source has multiple tables with related schemas requiring standardization.
- C. The source data is sensitive and requires role-based access control.
- D. You need to apply custom column-level transformations to a raw source.
Answer: B,D
Explanation:
yml files allow for complex source schemas and column transformations. Access control and loading strategies are usually handled at the database or project-level configuration.
NEW QUESTION # 256
A colleague asks, "Why do we need dbt docs when we already have good database documentation?" Provide a compelling response.
- A. dbt docs primarily serves as a replacement for dbt seed.
- B. dbt docs is mandatory for version control with dbt projects.
- C. dbt docs generates dynamic documentation that directly reflects your project's dependencies and current state.
- D. dbt docs automatically tracks model testing results.
Answer: C
Explanation:
Highlight how dbt docs offers up-to-date, project-specific documentation, while traditional database documentation can easily become outdated.
NEW QUESTION # 257
(Multiple Select)
- A. Data integration testing frameworks (e.g., Great Expectations)
- B. Tools specializing in schema change detection.
- C. Continuous Integration (Cl) tools.
- D. Anomaly detection platforms.
Answer: A,B,D
Explanation:
All of these address different aspects of advanced data validation that complement the basic tests within dbt. Cl tools (D) are involved in running these checks but are not the data validation tools themselves.
NEW QUESTION # 258
......
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