dbt Labs dbt-Analytics-Engineering Actual Tests : dbt Analytics Engineering Certification Exam

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. A colleague asks, "Why do we need dbt docs when we already have good database documentation?" Provide a compelling response.

A) dbt docs primarily serves as a replacement for dbt seed.
B) dbt docs is mandatory for version control with dbt projects.
C) dbt docs automatically tracks model testing results.
D) dbt docs generates dynamic documentation that directly reflects your project's dependencies and current state.

2. You encounter the following source configuration in a dbt_project.yml file. What kind of data source does this represent?

A) A raw table from your data warehouse.
B) A CSV file loaded as a seed.
C) An output from another dbt model.
D) An external data source connected via a dbt adapter.

3. A sudden data quality issue occurs in production. You need to quickly reproduce the problem in a lower environment but retain a point-in-time snapshot of production dat a. Which strategies might you employ? Create a backup of the production database and restore it to a separate development or testing database.

A) Use dbt snapshots to capture critical production tables during a defined timeframe for later use in troubleshooting.
B) A combination of the above, depending on time constraints and available resources.
C) Utilize data replication features (if supported by your data warehouse) to create a near real-time mirror of production data in a
D) staging area.

4. dbt Model Snippet:SQL

A) The source() function retrieving data from the incorrect schema.
B) Incorrect Jinja usage within a macro used for templating.
C) The SUM(order_amount) aggregation logic.
D) The GROUP BY month clause leading to duplicate rows.

5. (Multiple Select)

A) Submit an issue to the package's GitHub repository if its open-source.
B) Switch to a different dbt package offering similar functionality.
C) Temporarily override the buggy macro or model within your dbt project.
D) Update the packages_yml file to point to your forked version of the package.

Solutions: