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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
Managing Data Pipelines	15%	- CI/CD integration - Deployment strategies - Pipeline orchestration
Debugging and Error Resolution	15%	- Resolving data quality issues - Debugging techniques - Identifying modeling errors
Implementing dbt Tests	10%	- Test configuration and execution - Custom tests - Built-in tests
Creating and Maintaining Documentation	10%	- Documentation standards - Descriptions and metadata - Generating documentation
Developing dbt Models	20%	- Model optimization 1. Model contracts 2. Performance tuning - Model design and structure 1. Materialization types 2. Ref and source functions 3. Incremental models
dbt Models Governance	15%	- Project organization and structure - Naming conventions and standards - Version control integration
Leveraging dbt State	5%	- State-aware operations - State management
External Dependencies	10%	- External sources integration - Using packages - Managing snapshots

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q164-Q169):

NEW QUESTION # 164
you're working with a dbt project where a central model fct_orders is refactored. Several downstream models rely on this fact table. Which of the following is the MOST efficient way to determine which downstream models might be affected by this change?

A. Execute dbt run and observe for errors.
B. Use the dbt Is command to generate a lineage graph.
C. Manually review the code of all downstream models.
D. Run dbt test to see which tests might fail.
E. Utilize the dbt docs generate and dbt docs serve commands.

Answer: E

Explanation:
While options B, D, and E can indirectly hint at broken models, they're not the most efficient methods. The dbt docs commands allow you to directly visualize and explore dependencies within your dbt project, making it the ideal choice for this scenario.

NEW QUESTION # 165
You define a source table and include an override:YAML

A. The value 'my_project' is not a recognized keyword by dbt.
B. The overrides property needs to be defined at the source level, not the table level.
C. The overrides property is not valid for tables within your dbt_project.yml.
D. You need to create a macro named 'my_project' that contains the specific overriding logic.

Answer: B

Explanation:
While dbt supports overrides, they generally work at higher levels within your project file, not at the model level.

NEW QUESTION # 166
You've built a macro to implement a common custom test pattern. When using this macro in multiple models, you realize the tests are running much slower than expected. What might be the cause?

A. This is expected behavior, and custom tests always incur a performance penalty.
B. The macro's SQL logic is inefficiently querying the model or other data.
C. Too many tests are being defined on individual models.
D. The macro is accidentally triggering downstream model rebuilds.

Answer: B,C

Explanation:
Inefficient macro logic would be amplified with wide reuse. Having numerous tests, even simple ones, can add up. C is unlikely unless the macro directly references downstream models.

NEW QUESTION # 167
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. Replace the nested logic with a custom dbt macro to improve modularity.
D. Materialize the intermediate results of the subqueries as snapshots.

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 # 168
A user reports a critical security issue discovered in a third-party dbt package you use. Where could you most likely find updated information about potential vulnerabilities or fixes?

A. Directly from the maintainer of the dbt package, often in a GitHub repository or similar
B. The packages.yml file in your dbt project.
C. The locally generated dbt documentation for the installed packages.
D. Within dbt Cloud's central package documentation and release notes.

Answer: A

Explanation:
Package maintainers are the primary source of truth- However, options like A and C might provide additional resources:A. Your packages.yml might help identify the package C: dbt Cloud might aggregate some vulnerability information.

NEW QUESTION # 169
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