dbt Labs dbt Analytics Engineering Certification : dbt-Analytics-Engineering

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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You debug a production issue by running a model in a testing environment with additional logging output. Which dbt features or command-line additions would facilitate this?

A) dbt hooks to redirect model-related logs to a centralized logging platform.
B) Custom dbt flags (using -vars) to control the logging level of the SQL execution.
C) The -warn-error flag to treat warnings as errors, making your run fail louder on potential issues.
D) Environment variables to conditionally enable verbose logging macros inside the model.

2. (Multiple Select)

A) Your tests are likely configured to raise warnings rather than cause true errors.
B) Your dbt run command includes flags that override failing tests.
C) A 'post-hook' in your project configuration automatically fixes the issues flagged by tests.
D) Tests must be explicitly included in a model's test property for them to block model creation.

3. You discover that a heavily used model is taking significantly longer to materialize. After investigation, you determine that the complexity of the model's logic is a contributing factor. Which of the following actions is LEAST likely to help improve performance?

A) Investigate potential optimizations in the underlying SQL code.
B) Change the materialization from a table to a view.
C) Consider applying an incremental materialization strategy if suitable.
D) Break down the model into smaller, intermediate models using CTEs.

4. You discover a model sorting large amounts of data using an ORDER BY clause with several columns. Performance needs to be increased. What's the FIRST step in your optimization process?

A) Remove unnecessary columns from the ORDER BY clause.
B) Change the materialization from a 'table' to a 'view'.
C) Add a LIMIT clause to restrict the number of records sorted.
D) Examine query execution plans to identify bottlenecks and potential index usage.

5. You've defined a unique test on a key column within a model. When running dbt test, you encounter a surprising failure. Which of the following might be the cause?

A) An incorrect join in your model is inadvertently creating duplicate rows.
B) There are truly duplicate values in the column.
C) The unique test is too strict and doesn't align with the business definition of uniqueness.
D) Upstream data was updated unexpectedly, leading to previously non-existent duplicates.

Solutions: