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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
External Dependencies	10%	- Managing snapshots - External sources integration - Using packages
Implementing dbt Tests	10%	- Built-in tests - Test configuration and execution - Custom tests
Managing Data Pipelines	15%	- Pipeline orchestration - Deployment strategies - CI/CD integration
Debugging and Error Resolution	15%	- Resolving data quality issues - Debugging techniques - Identifying modeling errors
Creating and Maintaining Documentation	10%	- Generating documentation - Descriptions and metadata - Documentation standards
dbt Models Governance	15%	- Version control integration - Project organization and structure - Naming conventions and standards
Leveraging dbt State	5%	- State-aware operations - State management
Developing dbt Models	20%	- Model optimization 1. Performance tuning 2. Model contracts - Model design and structure 1. Incremental models 2. Ref and source functions 3. Materialization types

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q299-Q304):

NEW QUESTION # 299
You're experimenting with new transformations. You want to iterate on a model without affecting data in the production warehouse. Which dbt command should you use along with appropriate flags?

A. dbt test with -defer to temporarily bypass upstream dependencies.
B. dbt compile to ensure changes are valid without executing models.
C. dbt run with -target to specify a development environment.
D. dbt seed with -select to load data into production.

Answer: C

Explanation:
The -target flag allows you to isolate development work within different environments preventing accidental changes to production data.

NEW QUESTION # 300
You maintain a large dbt project with various reporting models that source data from a set of core business tables. These core tables often include columns with sensitive information. What technique could ensure compliance and maintainability when restricting access to this data?

A. Create incremental models that directly remove the sensitive columns before reporting models utilize them.
B. Use views to create different projections of the core tables, exposing only the necessary columns.
C. Apply row-level security within the data warehouse itself for fine-grained control.
D. Write complex WHERE clauses in each reporting model to exclude rows containing sensitive data.

Answer: B

Explanation:
Views provide a modular and maintainable way to define access restrictions. This approach centralizes the filtering logic, preventing repeated and potentially inefficient WHERE clauses across models.

NEW QUESTION # 301
You need to create a model that combines data from a large fact table with smaller dimension tables. Performance is paramount, and the data in the fact table updates incrementally but frequently. Which materialization strategy is likely to provide the optimal balance of efficiency and freshness?

A. Materialize the fact table as a table and the dimension tables as incremental models.
B. Materialize the fact table as an incremental model and the dimension tables as views.
C. Materialize all tables (fact and dimensions) as views.
D. Materialize all tables (fact and dimensions) as tables.

Answer: B

Explanation:
This approach leverages the strengths of different materializations. Incremental updates to the large fact table minimize processing, while views on the smaller dimension tables avoid unnecessary materialization costs.

NEW QUESTION # 302
You want to configure dbt to prevent tests from running if one or more of their parent models is unselected.
Which test command should you execute?
Choose 1 option.

A. dbt test --select "orders" --indirect-selection=empty
B. dbt test --select "orders" --indirect-selection=cautious
C. dbt test --select "orders"
D. dbt test --select "orders" --indirect-selection=buildable

Answer: A

NEW QUESTION # 303
Select the dbt materialization that typically DOES NOT persist its results to disk:

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

Answer: A

Explanation:
Ephemeral materializations are computed within CTEs (Common Table Expressions). Their results exist only during the query's execution and are useful for intermediate steps within complex transformations.

NEW QUESTION # 304
......

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