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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You need to run a custom Python script after your dbt models execute. Where and how can you configure this in your dbt_project.yml file?

A) Include the script as a 'seed' file with a specific execution order
B) Define it as a 'snapshot' to ensure it runs after all models.
C) Create an 'integration test' and use the PythonFunction class-
D) Utilize the on-run-end hook configuration.

2. You frequently need to spin up short-lived development environments on demand for testing and experimentation. Which dbt feature would streamline this process, especially when it involves custom configuration?

A) Creating multiple deployment environments in dbt Cloud.
B) dbt's -vars flag to override variable values.
C) dbt profiles defined in your dbt_project.yml file.
D) Using dbt tags to selectively execute parts of your project.

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

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

5. You write a macro to dynamically create a filter string and apply it within a model as follows:SQL

A) The database doesn't support comparison of the data type of the region column with a string value.
B) The generate_filter macro should be placed within a separate macros directory, not inline in the model.
C) The macro templating incorrectly nests single and double quotes.
D) You cannot dynamically apply filters using Jinja; they must be hardcoded in your model's SQL.

Solutions: