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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. (Multiple Select)

A) Your dbt tests are invalid.
B) You made a typo when defining the column name in your model.
C) A ref function referencing another model is incorrect.
D) An upstream source table schema was updated without updating the dbt model.

2. (Multiple Select)

A) Credentials used to authenticate to the data warehouse.
B) The target database schema where models are materialized.
C) The specific SQL dialect used when generating model code.
D) Availability of specific dbt packages used in your project.

3. Which of the following scenarios might warrant a git rebase instead of a standard git merge when integrating your changes into the main branch?

A) You need to resolve complex merge conflicts that arise during a standard merge.
B) You want to avoid a merge commit and keep a linear project history.
C) Your branch has diverged significantly from the main branch with unrelated changes.
D) You only want to include a subset of your feature branch commits in the main branch.

4. (Multiple Select)

A) You need to apply custom column-level transformations to a raw source.
B) The source has multiple tables with related schemas requiring standardization.
C) The source data is sensitive and requires role-based access control.
D) You want to test different loading strategies for a large source table.

5. You need to set up a production-like environment for load testing and performance tuning of dbt models. How might you approach the resource allocation and provisioning of this environment?

A) Write dbt macros that artificially increase dataset sizes in development for simulating load.
B) Run performance tests directly against production during a designated off-peak period.
C) Create a CI/CD job that dynamically scales a cloned production environment for the test, then scales it back down.
D) Partner with your data infrastructure team to get guidance based on their experience.

Solutions: