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| Section | Objectives |
|---|
| Testing and Data Quality | - Built-in and custom tests
- 1. Custom SQL tests
- 2. Generic tests (unique, not null, relationships)
- Data validation strategies
- 1. Schema testing practices
- 2. CI-based validation workflows
|
| Analytics Engineering Foundations | - Modern data stack concepts (ELT vs ETL)
- 1. Warehouse-centric transformation workflows
- 2. Role of dbt in analytics engineering
- SQL proficiency for analytics
- 1. Joins, aggregations, and window functions
- 2. Data modeling in SQL
|
| Deployment and Orchestration | - Environments and workflows
- 1. Development vs production environments
- 2. Version control with Git
- Running dbt in production
- 1. dbt Cloud and job scheduling
- 2. CI/CD integration patterns
|
| Documentation and Lineage | - Data lineage understanding
- 1. Dependency tracking with ref()
- 2. Directed acyclic graph (DAG)
- dbt documentation system
- 1. Model descriptions and metadata
- 2. Auto-generated docs site
|
| dbt Core Concepts | - Project structure and configuration
- 1. Packages and dependencies
- 2. dbt_project.yml configuration
- Models and materializations
- 1. Views, tables, incremental models
- 2. Ref and source functions
|
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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q29-Q34):
NEW QUESTION # 29
A complex transformation in your dbt project pulls data from an external API. Due to rate limits, this API endpoint cannot be queried frequently in production. How could you handle development and testing of this transformation effectively?
- A. Use environment variables to control API query frequency or switch between live and test data sources.
- B. Set up a development environment that utilizes a mock API to simulate external data.
- C. All of the above could be part of a strategy.
- D. Utilize dbt snapshots to capture a static set of API data for use during development and testing.
Answer: C
Explanation:
A: Mocks enable testing without impacting the production API- B: Environment variables allow for flexible configuration. C: Snapshots provide static samples for testing in isolation.
NEW QUESTION # 30
You want to trigger a dbt job immediately upon successful completion of an upstream ETL process. Which methods could achieve this?
- A. Scheduling a dbt job with a very frequent interval (e.g., every 5 minutes) to poll for changes in a metadata table.
- B. Configuring the ETL process to send a completion notification to your CIICD tool, triggering the dbt job.
- C. Using dbt Cloud's webhooks to create an endpoint that your ETL process can call.
- D. Using the dbt build command to run all dependent models after a successful dbt run.
Answer: B,C
Explanation:
A and B establish event-driven, active triggering. C is a workaround that may be inefficient and introduce a lag. D is for sequential execution, not external event dependency.
NEW QUESTION # 31
You have a large dataset that undergoes frequent, small updates. You need a model to quickly reflect these changes while minimizing resource usage. Which standard dbt materialization would be the BEST fit?
- A. Table
- B. Ephemeral
- C. Incremental
- D. View
Answer: C
Explanation:
Incremental models are ideal for this scenario. They only process the changed data, reducing the overall computational load compared to rebuilding the entire table each time.
NEW QUESTION # 32
A critical model fails with a non-descriptive error. You suspect a third-party package used in the model. How might you narrow down the problem?
- A. Temporarily disable the package and try running the model.
- B. Add -log-format json to your dbt run command to get more structured error output.
- C. Examine recent commits or releases of the package for changes that might have introduced a bug.
- D. Run the package's models in isolation to see if the error reproduces.
Answer: C
Explanation:
Start by understanding if the problem lies within the package itself. Disabling or isolating package models can help. Structured logging is useful for analysis.
NEW QUESTION # 33
Which two configuration items can be defined under models: in your dbt_project.yml file?
Choose 2 options.
- A. test
- B. target
- C. tags
- D. source
- E. schema
Answer: C,E
NEW QUESTION # 34
......
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