2026 dbt Labs dbt-Analytics-Engineering Key Concepts Pass Guaranteed Quiz
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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q98-Q103):
NEW QUESTION # 98
You've added detailed descriptions to your sources.yml file. Which of the following scenarios would still necessitate adding descriptions directly within your model files?
- A. If you want to provide additional context or logic specific to how a source is used within that model.
- B. If the source table undergoes a schema change, and you want to document these changes historically within the model.
- C. You always need both source and model-level descriptions for complete documentation.
- D. If different models utilize the same source table for different purposes.
Answer: A,B,D
Explanation:
A: Model descriptions allow for tailored explanations on how a source table is specifically used within the context of the model. B: Maintaining historical context of changes directly within the model can be valuable for traceability. C: Differing model use cases can warrant distinct descriptions for the same source table.
NEW QUESTION # 99
You've meticulously added descriptions and tests to your dbt models. However, after running dbt docs generate, the tests don't appear in the generated documentation. Which of the following reasons are most likely?
- A. You are using a custom schema test macro that isnt configured to be included in the documentation.
- B. Your tests have incorrect syntax, and dbt is silently skipping them during documentation generation.
- C. The dbt_project.yml file may not have the appropriate settings for including tests in the documentation.
- D. There is a bug in the version of dbt you're using that specifically affects test rendering in documentation.
Answer: A,C
Explanation:
A: Custom macros often need explicit configuration to be included in the generated documentation. C: The dbt_project.yml file controls which elements (models, tests, etc.) are included in the docs- You'll need to verify the relevant settings.
NEW QUESTION # 100
You debug a production issue by running a model in a testing environment with additional logging output. Which dbt features or command-line additions would facilitate this?
- A. dbt hooks to redirect model-related logs to a centralized logging platform.
- B. Custom dbt flags (using -vars) to control the logging level of the SQL execution.
- C. Environment variables to conditionally enable verbose logging macros inside the model.
- D. The -warn-error flag to treat warnings as errors, making your run fail louder on potential issues.
Answer: B,C,D
Explanation:
These provide control during execution:A changes model behavior. B makes execution more sensitive. C alters dbt's log handling.
NEW QUESTION # 101
After running dbt docs generate, you notice that your project documentation looks incomplete, and certain details seem to be missing. Which of the following actions could help you troubleshoot the issue?
- A. Verify that all your models, sources, seeds, and tests have descriptions where appropriate.
- B. Check if you've unintentionally used the -select flag to limit model inclusion during a previous dbt run.
- C. Run the dbt clean command to clear out any outdated artifacts.
- D. Ensure all relevant model directories are present under the top-level 'models' directory of your dbt project
Answer: A,B,D
Explanation:
A Missing descriptions for elements within your project will directly impact the completeness of the generated documentation. B: Residual -select flags from previous runs might limit the models that dbt processes for the documentation. C: dbt's standard structure assumes a 'models' directory for discovering models. Incorrect placement could interfere with the documentation generatiom
NEW QUESTION # 102
Your team sometimes defines raw data sources directly in dbt models using .yml files within the models directory. When might this approach be problematic?
- A. If the raw dataset is accessed via a non-standard data warehouse connector.
- B. If the raw dataset's schema is subject to change.
- C. If the raw dataset requires complex transformations.
- D. If multiple models utilize the same raw dataset.
Answer: D
Explanation:
Defining raw sources within models leads to duplication and potential maintenance issues when multiple models share that dependency. A separate sources.yml file is generally preferred for shared datasets.
NEW QUESTION # 103
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