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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q291-Q296):

NEW QUESTION # 291
You accidentally pushed a large file containing sensitive data to a public remote repository. What immediate actions should you take?

A. Use git reset -hard to revert the commit and remove the file locally.
B. Contact the repository hosting service for assistance.
C. Both B and C.
D. Permanently remove the sensitive file from Git history using tools like git filter-branch.

Answer: B,D

Explanation:
B: You must ensure the sensitive data is completely removed from the history of the repository. C: The hosting service might have additional security measures or be able to assist in preventing the sensitive data from being accessed

NEW QUESTION # 292
You want to trigger a dbt job immediately upon successful completion of an upstream ETL process. Which methods could achieve this?

A. Using the dbt build command to run all dependent models after a successful dbt run.
B. Configuring the ETL process to send a completion notification to your CIICD tool, triggering the dbt job.
C. Using dbt Cloud's webhooks to create an endpoint that your ETL process can call.
D. Scheduling a dbt job with a very frequent interval (e.g., every 5 minutes) to poll for changes in a metadata table.

Answer: B,C

Explanation:
A and B establish event-driven, active triggering. C is a workaround that may be inefficient and introduce a lag. D is for sequential execution, not external event dependency.

NEW QUESTION # 293
You're onboarding a new dbt project to an existing production database. You find tables that might conflict with naming conventions used by dbt. What's a proactive way to handle this?

A. Update your dbt models to use aliases that avoid the name collisions.
B. Add configuration settings to your database connection profile instructing dbt to use a specific schema prefix.
C. Customize the schema property in your dbt_project.yml to namespace dbt-generated objects.
D. Manually rename the conflicting tables in the database prior to running any dbt jobs.

Answer: C

Explanation:
A isolates dbt's output in a dedicated way. B is less common, C risks breaking existing applications, D is more tedious.

NEW QUESTION # 294
You've created a pull request, and a discussion in the code review reveals issues with the approach you used in your feature branch. Rather than continuously updating the original branch, what's a strategy to address the feedback while keeping a clean pull request history?

A. Directly modify the commits on your existing feature branch using git rebase -i.
B. Request that your collaborators edit the code directly within the pull request interface.
C. Close the original pull request and create a new branch with the revised implementation.
D. Add the changes as a new commit to your feature branch, explaining the revisions in the pull request comments.

Answer: C

Explanation:
A: A new branch often provides the cleanest history for the reworked feature. B: Altering existing commits should be used judiciously, as it 'rewrites' history and can cause problems for collaborators.

NEW QUESTION # 295
A new stakeholder needs to receive an email report generated from the results of a specific dbt model. Unfortunately, your Bl tool doesn't directly integrate with dbt. How could you address this?

A. Write a post-hook that queries the model, formats the results, and sends the email.
B. Modify the model to output a CSV file and schedule a task to email the file as an attachment
C. Within the model's SQLi write logic to insert the output data into a dedicated reporting table-
D. Develop a separate script, triggered after the dbt job, to handle report generation and emailing-

Answer: A,C,D

Explanation:
Each provides a means to get the data outA does it within dbt workflow B uses an external tool for the non- dbt task. C leaves the data ready for other tools. D is clumsy and adds storage overhead.

NEW QUESTION # 296
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