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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q146-Q151):

NEW QUESTION # 146
You introduce a custom macro into your project. This is a snippet of your dbt_project.yml:YAML

A. The .sql extension on the file within the macros directory is incorrect.
B. The macro's name should only be 'trim', without the 'string_utils' prefix.
C. The macro_paths configuration in your dbt_project.yml might be incorrect or missing.
D. You must place the macros directory within the root of your dbt project.

Answer: C

Explanation:
Check your macro file paths, as an incorrect configuration would prevent dbt from finding the macro. The others are likely not the issue but worth double-checking.

NEW QUESTION # 147
A team member has opened a pull request, but conflicts arise when you attempt to merge it. Which of the following are essential steps in the conflict resolution process?

A. Communicate with your team member to understand the intent behind the conflicting changes.
B. Utilize Git's built-in merge conflict markers to identify areas of disagreement
C. Manually edit the affected files in your favorite text editor to resolve the differences.
D. All of the above.

Answer: D

Explanation:
A: You'll need to carefully edit files to combine the changes correctly. B: Git conflict markers visually highlight where conflicts need to be addressed. C: Communication is key to determining the best way to reconcile conflicting changes and maintain code intent.

NEW QUESTION # 148
A project stakeholder requests access to an intermediate stage of a dbt transformation pipeline to validate specific calculations.
You need to weigh this request carefully because:

A. All of the above-
B. Exposing intermediate results can lead to premature analysis based on incomplete data.
C. Granting access to intermediate data may confuse stakeholders who are not familiar with the full transformation process-
D. Raw data, development data, and production data often have different levels of data quality, completeness, and timeliness.

Answer: B

Explanation:
A: Intermediate data might be unrefined and not suitable for decision-making. B: Stakeholders might misinterpret the context of intermediary data. C: It's vital to guide stakeholders to final data outputs designed for analysis.

NEW QUESTION # 149
You discover a model sorting large amounts of data using an ORDER BY clause with several columns. Performance needs to be increased. What's the FIRST step in your optimization process?

A. Change the materialization from a 'table' to a 'view'.
B. Examine query execution plans to identify bottlenecks and potential index usage.
C. Add a LIMIT clause to restrict the number of records sorted.
D. Remove unnecessary columns from the ORDER BY clause.

Answer: B

Explanation:
Before implementing changes, it's crucial to understand current performance bottlenecks. Query execution plans provide this insight.

NEW QUESTION # 150
You're planning your production dbt deployment strategy. When deciding between completely separate development and deployment environments vs. using different schemas within a single data warehouse, what are I key factors to weigh?

A. The desired level of isolation and access control granularity.
B. The complexity of your dbt project and the number of models.
C. The need to collaborate between developers with varying skill levels.
D. Your data warehouse's pricing model and how it charges for resource usage.

Answer: A,C,D

Explanation:
B speaks to security and change management. C is important as the cost could differ considerably. D influences the need for stronger isolation. A is less important than the others here.

NEW QUESTION # 151
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