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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Managing Data Pipelines	15%	- CI/CD integration - Pipeline orchestration - Deployment strategies
Topic 2: dbt Models Governance	15%	- Naming conventions and standards - Version control integration - Project organization and structure
Topic 3: Implementing dbt Tests	10%	- Test configuration and execution - Built-in tests - Custom tests
Topic 4: Creating and Maintaining Documentation	10%	- Generating documentation - Documentation standards - Descriptions and metadata
Topic 5: Leveraging dbt State	5%	- State management - State-aware operations
Topic 6: Developing dbt Models	20%	- Model optimization 1. Performance tuning 2. Model contracts - Model design and structure 1. Materialization types 2. Ref and source functions 3. Incremental models
Topic 7: External Dependencies	10%	- Using packages - External sources integration - Managing snapshots
Topic 8: Debugging and Error Resolution	15%	- Debugging techniques - Identifying modeling errors - Resolving data quality issues

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q340-Q345):

NEW QUESTION # 340
After configuring a dbt package, you notice its models depend on a source table absent from your warehouse. How do you typically address this?

A. Rewrite the package's model from scratch within your project to remove the dependency.
B. Update your source definitions to include the required table.
C. File an issue or submit a pull request to the package's repository.
D. Override the package model's SQL query to reference an existing table in your warehouse.

Answer: D

Explanation:
Start by fulfilling the package's dependencies. If the table is truly generic, then customizing the SQL (B) might be the next step.

NEW QUESTION # 341
Outdated Macro

A. Write unit tests to validate the macro's output with a variety of input scenarios, including edge cases.
B. Deploy the modified macro to a staging environment and run a representative subset of dbt models.
C. Create a new source table specifically for testing the macro without impacting production data.
D. Run dbt Is to identify all locations where the macro is used and ensure compatibility.

Answer: A,B

Explanation:
Unit tests isolate the macro's logic, while a staging environment allows for real-world impact assessment. A separate source table might be overkill; dbt Is focuses on dependencies, not functionality.

NEW QUESTION # 342
You introduce a minor formatting change to a large SQL model. Afterwards, the results change unexpectedly. Which dbt-related issue might explain this, even if the SQL itself appears correct?

A. You've used a reserved keyword as a column alias without properly quoting it.
B. An upstream data issue only surfaces due to the formatting change making that part of the query execute differently.
C. There's a version mismatch between the dbt library used during development and in production.
D. A subtle indentation change in a CTE accidentally modifies the execution order within the query.

Answer: D

Explanation:
Whitespace matters in SQL, and CTE order is often significant even if the query might still be validly formatted.

NEW QUESTION # 343
You're debugging a runtime error. Analyzing the compiled SQL alone doesn't provide enough clues to find the root cause. What's your next debugging step?

A. Examine the dbt logs for more context about the model's execution and dependencies.
B. Compare compiled SQL from a previous successful run to the current failing version-
C. Disable custom macros to see if one of them is interfering-
D. Modify the compiled SQL directly and re-run the query against your warehouse.

Answer: A

Explanation:
Logs often provide additional error messages and context Comparing SQL versions can be helpful but might not illuminate the root cause. Never modify compiled SQL directly

NEW QUESTION # 344
Your team decides to use separate databases within the data warehouse for development, staging, and production. Which are the potential benefits of this approach?

A. The ability to fine-tune database configurations and permissions specifically for each environment's purpose.
B. All of the above.
C. Increased isolation of changes between environments, reducing the risk of unintended consequences in production.
D. Simplified testing and deployment processes due to clear separation of environments.

Answer: B

Explanation:
A: Isolation minimizes risks of production interference. B: Tailored configuration optimizes performance or security per environment. C: Clean separation streamlines operations and workflows.

NEW QUESTION # 345
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