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

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. While onboarding new data sources to your dbt project, you discover some have unexpectedly high null rates in key columns. How would you integrate tests for this into your dbt workflow?

A) Create not_null tests on the raw source tables in a separate dbt project dedicated to source validation.
B) Include a data quality monitoring step in your upstream ETL process before data reaches dbt
C) Designate some nulls as acceptable by extending the not_null test with the OR condition.
D) Write tests within the initial staging models that calculate and check the null percentage.

2. You need to run a dbt job that performs a long-running data cleansing operation. The job occasionally times out. Which of the following are potential solutions?

A) Use a dbt macro to retry the cleansing operation with a backoff strategy within the model itself-
B) Increase the timeout setting in your CI/CD tool or dbt job configuration.
C) Break the cleansing logic into multiple models, chaining them with dependencies-
D) Schedule the job to run concurrently with other dbt models to maximize resource usage-

3. You're refactoring a project with long model files containing intertwined logic. Which of the following is NOT a typical sign of a good candidate for applying modularity principles?

A) The same SQL patterns are repeated with minor variations.
B) Portions of the logic form distinct conceptual steps in the transformation process.
C) Renaming code blocks would improve readability.
D) The models are relatively small and perform simple transformations.

4. You've included the popular 'dbt-utils' package in your project. Where should you primarily expect to find the models and macros it offers?

A) In the 'dbt_project.yml' file under a 'packages' section.
B) Within the 'seeds' directory of your dbt project.
C) Automatically materialized as new tables in your data warehouse.
D) Within your 'models' directory namespaced to distinguish them from your own models.

5. You encounter the following source configuration in a dbt_project.yml file. What kind of data source does this represent?

A) An output from another dbt model.
B) An external data source connected via a dbt adapter.
C) A CSV file loaded as a seed.
D) A raw table from your data warehouse.

Solutions: