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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Objectives
Analytics Engineering Foundations	- Modern data stack concepts (ELT vs ETL) 1. Role of dbt in analytics engineering 2. Warehouse-centric transformation workflows - SQL proficiency for analytics 1. Joins, aggregations, and window functions 2. Data modeling in SQL
Deployment and Orchestration	- Environments and workflows 1. Development vs production environments 2. Version control with Git - Running dbt in production 1. dbt Cloud and job scheduling 2. CI/CD integration patterns
dbt Core Concepts	- Models and materializations 1. Ref and source functions 2. Views, tables, incremental models - Project structure and configuration 1. dbt_project.yml configuration 2. Packages and dependencies
Documentation and Lineage	- Data lineage understanding 1. Directed acyclic graph (DAG) 2. Dependency tracking with ref() - dbt documentation system 1. Auto-generated docs site 2. Model descriptions and metadata
Testing and Data Quality	- Built-in and custom tests 1. Custom SQL tests 2. Generic tests (unique, not null, relationships) - Data validation strategies 1. CI-based validation workflows 2. Schema testing practices

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q167-Q172):

NEW QUESTION # 167
You must exclude a specific model from being included in the generated documentation entirely. How would you achieve this?

A. Its not possible to exclude individual models; you can only exclude entire folders.
B. Remove all descriptions and tags associated with the model.
C. Add a dæs: {enabled: false} entry to the model's YAML configuration.
D. Use the enabled flag in your dbt_projectyml file to control model inclusion.

Answer: D

Explanation:
The enabled flag in dbt_project.yml provides control over whether a model (or other resources) are includedin dbt operations, including doc generation. Check your dbt version documentation for the latest syntax

NEW QUESTION # 168
You have a dbt macro that generates a list of models to execute dynamically. Which dbt command should you use in conjunction with this macro to actually run those models?

A. dbt Is to retrieve project metadata and feed it into your custom execution logic.
B. dbt debug to step through model execution while using the macro's output
C. dbt parse to pre-compile the project graph, allowing model selection by reference.
D. dbt build to create a task graph, extracting model nodes, and running them as needed.

Answer: C

Explanation:
A makes the dbt graph available, including macros, during execution- B gets metadata, but not for execution. C helps troubleshoot, but not run macros. D isn't designed for dynamic macro output

NEW QUESTION # 169
A colleague has introduced a new sensitive column into a source table. You need to update the dbt project documentation accordingly. Which of the following actions should you take?

A. Update the source documentation and add references to that documentation in the appropriate model's YAML file
B. Consult your organization's data governance policies and consider additional measures beyond simple documentation.
C. Add a clear description of the sensitive column in its corresponding YAML file.
D. Add the column description and tag it using a custom sensitive tag in the YAML file.

Answer: A,B,D

Explanation:
B). Tagging sensitive data helps categorize it, allowing for potential filtering or access control within the documentation. C: Handling sensitive data goes beyond simple documentation. Its crucial to follow your organization's data security and governance protocols. D: Referencing source documentation provides full context and traceability of the sensitive data's origin.

NEW QUESTION # 170
You're working in a large, enterprise-level dbt deployment. Which aspect of using dbt documentation commands could become especially important in this context?

A. Developing strict documentation contribution guidelines for multiple teams and collaborators.
B. All of the above.
C. Version-controlling your documentation changes alongside your project code.
D. Optimizing the dbt docs generate process for very large projects to minimize execution time.

Answer: B

Explanation:
All aspects become increasingly important in larger projects:A: Optimization matters when many models create more complex documentation. B: Tracking documentation history alongside code is crucial for governance. C: Clear guidelines are essential with many contributors.

NEW QUESTION # 171
Collaborative Fix

A. Include updated model documentation (dbt docs) outlining the logic and reasons for adjustment.
B. All of the above.
C. Open a pull request with detailed comments explaining the rationale for the changes and any potential side-effects.
D. Add clear commit messages that concisely summarize the purpose of the fix.

Answer: B

Explanation:
Changes need context! I-Jse comments, updated docs, and informative commit messages.

NEW QUESTION # 172
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