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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Documentation and Lineage | - Data lineage understanding
|
| Analytics Engineering Foundations | - Modern data stack concepts (ELT vs ETL)
|
| Deployment and Orchestration | - Running dbt in production
|
| Testing and Data Quality | - Data validation strategies
|
| dbt Core Concepts | - Models and materializations
|
dbt Labs dbt Analytics Engineering Certification Sample Questions:
dbt Model Snippet:SQL
- A. Your sources.yml file is not configured correctly-
- B. Your dbt_projectyml file has a model-level schema override.
- C. There's a custom macro in use that dynamically changes schemas.
- D. The stg_orders model uses a schema config in its own model SQL
Correct Answer: B 🗳️
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You must exclude a specific model from being included in the generated documentation entirely. How would you achieve this?
- A. Add a dæs: {enabled: false} entry to the model's YAML configuration.
- B. Use the enabled flag in your dbt_projectyml file to control model inclusion.
- C. Remove all descriptions and tags associated with the model.
- D. Its not possible to exclude individual models; you can only exclude entire folders.
Correct Answer: B 🗳️
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You need a way to document relationships between raw source tables, dbt models, and downstream Bl dashboards. What type of tool would be best suited for this task?
- A. dbt's built-in documentation (dbt docs)
- B. A data profiling tool
- C. A version control system
- D. A data catalog
Correct Answer: D 🗳️
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(Multiple Select)
- A. Utilize window functions to efficiently compute the difference without self-joins.
- B. Pre-calculate frequently used periods (e.g., current month, previous month) and store them as intermediate CTEs.
- C. Ensure relevant columns in underlying tables have appropriate indexes.
- D. Introduce redundant columns in source tables to store pre-calculated percentage changes.
Correct Answer: A,C 🗳️
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A model depends heavily on geospatial calculations, which are computationally expensive. What optimization strategy might be worth exploring?
- A. Investigate whether the database offers specialized geospatial indexes or functions.
- B. Ensure the underlying data adheres to DRY principles.
- C. Convert the model to a snapshot to leverage historical data more effectively.
- D. Pre-calculate common geospatial results as an incremental model.
Correct Answer: A 🗳️
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