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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. Your fct_orders model depends on both raw_sales and stg_customers. Due to upstream changes, the customer_id column in raw_sales is now named cust_id. How could you manage this change with minimal disruption?

A) Update the fct_orders model to reference cust_id.
B) Create an alias for customer_id as cust_id in the stg_customers model.
C) Use a dbt source to rename the column in raw sales.
D) Utilize dbt's ref() function to dynamically adapt to the new column name.

2. Your team establishes a policy for handling different levels of test failures (e.g., warnings vs. critical errors). How could you implement this policy effectively within your dbt workflows?

A) Run dbt test multiple times with varying filters based on desired severity levels.
B) Use custom severity levels in your test definitions and a post-hook to manage actions accordingly.
C) Use dbt tags for classifying tests, then selectively execute them.
D) Rely on your data observability platform to differentiate and alert based on dbt test results.

3. You want to implement a macro that displays a warning icon next to models in the DAG that haven't been tested. Which of the following would be necessary to make this work?

A) All of the above.
B) A custom CSS class for the warning icon and a way to apply it dynamically using the macro.
C) Configuration in your dbt_projectyml file to associate models with the relevant tests.
D) The ability for the macro to query the results of test executions from the dbt run-

4. A performance-critical model depends on multiple complex transformations that would benefit from being pre-computed. Direct querying of this model should be as fast as possible. Which materialization is likely the best choice?

A) Incremental
B) View
C) Table
D) Ephemeral

5. You get a warning during dbt run:WARNlNG: Found 100 rows in 'stg_customers' that will become duplicates in the 'dim_customers' target.

A) Update the stg_customers source definition to include filtering logic to remove duplicate rows.
B) It's safe to ignore this warning, as de-duplication is handled automatically by dbt.
C) Increase the memory allocated for the database to handle the large number of duplicates.
D) Investigate your dim_customers modeling logic to ensure a unique key is correctly used to prevent duplicates.

Solutions: