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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. A source table is updated with a full overwrite every night. Your dbt job fails due to freshness checks. What's a likely cause and solution?

A) You need to schedule the dbt job to run after the nightly update.
B) The freshness check is misconfigured- Adjust the count and period settings.
C) The loaded_at field is absent Add the corresponding column or remove the check-
D) The source uses an incremental materialization. Change it to a 'table'

2. A project relies on multiple external data sources with varying update frequencies (some daily, some hourly, some near real-time). How might you approach designing your dbt environments to efficiently handle these sources?

A) Use separate dbt targets for each source type based on update frequency to optimize run schedules.
B) Consider staging data in your data warehouse with varying materialization strategies, allowing for streamlined transformation logic in dbt.
C) Utilize incremental models and orchestration features provided by dbt to minimize unnecessary reprocessing of data.
D) All of the above could contribute to an effective solution.

3. You're collaborating on a project where team members have varying levels of dbt experience. How can you use the dbt_project.yml to help standardize practices?

A) Define custom macros in the project file to encapsulate commonly used SQL patterns.
B) Include a docs: section with detailed descriptions of core models and transformations.
C) Set up pre-commit hooks within the project file to enforce linting and formatting rules.
D) Configure project-level tests to ensure adherence to data quality standards.

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

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

5. 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) View
B) Ephemeral
C) Table
D) Incremental

Solutions: