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| Section | Weight | Objectives |
|---|
| Models | 25% | - Seeds - Sources and references - Writing and managing SQL models - Snapshots - Materializations (table, view, ephemeral, incremental)
|
| Testing and Documentation | 20% | - Documentation generation - Custom data tests - Schema tests (unique, not_null, accepted_values, relationships) - dbt docs and DAG visualization
|
| Data Transformation Techniques | 25% | - Macros and packages - Jinja templating - Common table expressions and subqueries - Refactoring and incremental models
|
| Deployment and Orchestration | 15% | - Git version control integration - Jobs and scheduling in dbt Cloud - CI/CD with dbt Cloud - Environments (dev, staging, prod)
|
| dbt Fundamentals | 15% | - dbt Core vs dbt Cloud - dbt project structure - dbt workflow and best practices
|
>> dbt-Analytics-Engineering Latest Test Questions <<
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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q337-Q342):
NEW QUESTION # 337
You want to display the runtime metrics (e.g., execution time) of each model directly on the DAG node. Which challenges might you face when implementing this?
- A. dbt documentation is primarily static; it might not be able to render dynamic metrics that change with each execution.
- B. Adding too much detailed information directly to the DAG could lead to visual clutter and make it overwhelming.
- C. All of the above
- D. Retrieving runtime metrics for each historical run might not be natively supported by dbt
Answer: C
Explanation:
A: You might need to generate static summaries or find workarounds to display dynamic metrics. B. Collecting runtime metrics across all historical runs might require additional logging or integration with dbt artifacts (manifestjson, run_resultsjson)- C: The DAG visualization needs a balance between information and readability.
NEW QUESTION # 338
You've implemented the built-in dbt.get_column_values macro to display sample data values from a source column directly on the DAG. However, you notice performance issues when loading the docs. Which optimization strategy could you consider?
- A. Replace dbt_get_column_values with a custom macro that only fetches the first few sample values.
- B. Utilize a dbt snapshot to materialize the macro results instead of computing them on the fly.
- C. Increase the compute resources allocated to your dbt documentation generation process.
- D. Modify the macro to only retrieve sample values during development and not for production documentation.
Answer: A,B,D
Explanation:
B: Disabling expensive computations conditionally can boost performance for production environments. C: Snapshots pre-compute values, potentially improving DAG loading times. D: Reducing the amount of data retrieved by the macro could help with performance.
NEW QUESTION # 339
A colleague asks, "Why go through the trouble of using dbt? Can't we just write SQL scripts and schedule them?" Which of the following is the most compelling argument for using dbt?
- A. dbt offers native support for advanced scheduling and orchestration features.
- B. dbt models are typically more performant than hand-written SQL scripts.
- C. dbt automatically generates user-friendly data lineage visualizations.
- D. dbt promotes modularity, reusable code, and testing within data transformation pipelines.
Answer: D
Explanation:
While other options have benefits, dbt's core strength lies in enforcing structure and maintainability in data transformation processes.
NEW QUESTION # 340
You encounter a dbt model using a series of nested subqueries to achieve complex filtering. Performance is poor. Which common alternative is likely to provide a performance boost?
- A. Rewrite the subqueries into equivalent JOIN statements where possible.
- B. Convert subqueries into nested CTEs for better readability.
- C. Materialize the intermediate results of the subqueries as snapshots.
- D. Replace the nested logic with a custom dbt macro to improve modularity.
Answer: A
Explanation:
Databases typically optimize joins more effectively than deeply nested subqueries. The other options don't directly address the core performance issue.
NEW QUESTION # 341
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. The default materialized setting defined for models in your dbt_project_yml file.
- C. If this is a one-time need, or something requiring scalable permission management.
- D. The database technology and its permissions model.
Answer: A,C,D
Explanation:
Each of these shapes the specific implementation-A impacts how you'll write the GRANT. B is about a layer of control. C is about ad-hoc vs. integrated security.
NEW QUESTION # 342
......
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