dbt Labs dbt Analytics Engineering Certification - dbt-Analytics-Engineering

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

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

2. 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) Custom dbt flags (using -vars) to control the logging level of the SQL execution.
B) The -warn-error flag to treat warnings as errors, making your run fail louder on potential issues.
C) Environment variables to conditionally enable verbose logging macros inside the model.
D) dbt hooks to redirect model-related logs to a centralized logging platform.

3. You discover an intermittent issue where your models sometimes produce incorrect results. After investigation, the problem seems to occur when the source data contains a particular combination of unexpected values. How would you best address this?

A) Raise an issue with the team responsible for the upstream data source to fix the error at its origin.
B) Add pre-processing logic within the model to clean or filter out the problematic data.
C) Write a custom dbt test to explicitly identify the bad data scenario.
D) Modify the model to ignore the rows causing the issue.

4. (Multiple Select)

A) Catching subtle errors or discrepancies that may not cause immediate functional issues.
B) Validating changes during development before deploying a new dbt model version.
C) Ensuring data synchronization after a migration.
D) Testing performance under a simulated heavy load.

5. Which of the following are essential elements of a well-structured pull request description?

A) A concise title summarizing the overall changes.
B) References to related issues in the project tracker, if applicable.
C) Explanations of the reasoning behind major changes and implementation choices.
D) Detailed logs of each Git command used during development.

Solutions: