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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You've defined a complex custom singular test. While testing it initially on a development dataset, it times out. Which optimization techniques might be worth trying?

A) Remove any redundant joins or subqueries from the test logic.
B) Disable the test in production environments and run it only in development.
C) Ensure the test SQL uses appropriate indexes in the underlying database.
D) Rewrite the test using a dbt macro for better maintainability.

2. You're setting up baseline comparisons with historical dat
a. Which factors are crucial to consider when selecting or generating the baseline dataset?

A) The baseline should cover a representative time range relevant to your analysis.
B) If using data, the baseline might need sanitization to remove PII-
C) The baseline needs to align in structure (schemas) with the dbt models being tested.
D) The data volume in the baseline should be large enough to identify statistical patterns.

3. (Multiple Select)

A) Misspelling "orders" as "orderes".
B) Using an 's' at the end of tables.
C) The error_after freshness check syntax.
D) Indenting freshness incorrectly under the customers table.

4. The dataset you work with contains personally identifiable information (PII). Which types of additional tooling might be necessary for your project beyond a core dbt implementation?

A) Advanced statistical modeling tools.
B) Data masking or tokenization solutions.
C) Enhanced data access governance and auditing tools.
D) Automated ETL pipelines

5. A model refactors a frequently used SQL calculation. Traditionally this logic was copied across multiple models. Which of the following is the LEAST likely benefit of refactoring this calculation into a macro?

A) Simplified dependency tracking
B) Improved readability of models
C) Reduced error potential due to a single source of logic
D) Faster dbt job execution time

Solutions: