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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You suspect discrepancies due to potential changes in upstream source tables. What's a practical first step to investigate?

A) Compare the current state of the source tables against their historical snapshots.
B) Contact the team responsible for managing the sources to inquire about recent updates.
C) Run all dbt models and examine the logs for unusual entries.
D) Review the dbt project's manifest.json for related changes.

2. (Multiple Select)

A) Ensuring column ordering matches an external specification.
B) Validating that the row count of the staging model falls within an expected range.
C) Enforcing specific ratios or relationships between aggregated values.
D) Checking for referential integrity with a separate lookup table.

3. Select the dbt materialization that typically DOES NOT persist its results to disk:

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

4. Which types of transformations are often best suited for raw data as an initial step in your dbt project?

A) Both A and C-
B) Casting and typecasting of columns to ensure consistent data types-
C) Renaming columns and performing basic data cleaning
D) Applying business logic and complex aggregations for reporting purposes.

5. A model intermittently fails. Sometimes it runs without errors. Which category of issue should you suspect FIRST?

A) dbt-specific configuration errors causing unpredictable behavior at the engine level.
B) Race conditions due to models in your DAG running concurrently without proper synchronization.
C) Data quality issues in the source that are not consistently present.
D) Errors within complex macros used by the model, triggered only under specific data conditions.

Solutions: