dbt Labs dbt-Analytics-Engineering exam practice questions and answers

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q286-Q291):

NEW QUESTION # 286
You've configured your project to include both schema and data tests in the generated documentation. A user reports the tests are visible but don't show any execution results (pass/fail status). Why might this be happening?

A. The project settings are explicitly configured to hide test results in the documentation.
B. Your data pipeline hasn't been executed recently, so there are no recent test results.
C. The type of test you're using is not supported for displaying results in the documentation.
D. The documentation generator has a known limitation on how test results are displayed.

Answer: A,B

Explanation:
A Test results depend on recent executions; if your data pipeline is not updated, there won't be fresh results. B: Its possible to have configurations that display the tests themselves but not their execution results

NEW QUESTION # 287
(Multiple Select)

A. Schema tests to confirm the existence of tables and columns.
B. not_null and unique tests on primary key columns.
C. Tests checking for row count discrepancies between source systems and target tables.
D. Tests comparing the latest data against historical baselines.

Answer: A,B,C

Explanation:
A, B, and C focus on verifying basic data transfer and structural integrity. D is important, but comes after making sure the data is there at all_

NEW QUESTION # 288
(Multiple Select)

A. Using credentials with appropriate permissions (likely read-only) to access production data sources.
B. Scheduling models to run outside normal business hours to reduce resource contention.
C. Implementing more rigorous access controls and auditing procedures.
D. Potentially running on a different data warehouse or with different database settings.

Answer: A,C,D

Explanation:
A reflects the increased security needs of production environments. B allows scaling or optimization based on workload. C prevents accidental changes in production. D is a strategy, but not a fundamental difference.

NEW QUESTION # 289
You're testing a model containing financial calculations. Your stakeholders require a high degree of accuracy. Which consideration is most important when designing tests for this scenario?

A. Implementing a large number of generic tests to provide basic coverage.
B. Understanding acceptable tolerances and writing tests to check values within a defined range rather than exact matches.
C. Using floating-point-specific equality checks for calculated values.
D. Ensuring tests cover a comprehensive range of input scenarios and edge cases.

Answer: B,D

Explanation:
B recognizes that financial calculations often have rounding imprecision, necessitating tolerance-based checks. C is crucial as even minor input variations can propagate into significant errors for financial models. A is generally a bad practice; D focuses on quantity, not the specific quality needed here.

NEW QUESTION # 290
During a code review, a collaborator suggests modifying a small portion of code you had already committed to your feature branch. What's the most efficient way to address this without creating a completely new commit?

A. Use git commit -amend to modify your most recent commit.
B. Explain to your collaborator that modifying committed code is not recommended, and the change should wait for a future update.
C. Use git revert to undo your previous commit, make the change, and then re-commit.
D. Create a new branch extending from your feature branch, make the change, and open a separate pull request.

Answer: A

Explanation:
Git commit -amend allows seamless modification of your most recent commit, preserving a clean commit history.

NEW QUESTION # 291
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