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| Section | Objectives |
|---|---|
| Topic 1: Deployment and Orchestration | - Running dbt in production
|
| Topic 2: Testing and Data Quality | - Built-in and custom tests
|
| Topic 3: Documentation and Lineage | - dbt documentation system
|
| Topic 4: dbt Core Concepts | - Models and materializations
|
| Topic 5: Analytics Engineering Foundations | - SQL proficiency for analytics
|
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NEW QUESTION # 319
You need to run a dbt job that performs a long-running data cleansing operation. The job occasionally times out. Which of the following are potential solutions?
Answer: A,C,D
Explanation:
Each tackles the timeout issue differently:A reduces the work done in a single step. B provides more time directly . C adds retry resilience within the logic. D would likely worsen performance due to resource contention.
NEW QUESTION # 320
Which two configuration items can be defined under models: in your dbt_project.yml file?
Choose 2 options.
Answer: D,E
Explanation:
The correct answers are A: schema and C: tags.
In dbt, the dbt_project.yml file is the central configuration file that defines model-level settings. Under the models: section, you can specify a wide range of model configurations such as schema, materialized, tags, alias, and custom meta fields. The schema configuration allows you to control which database schema a model should be built in, giving analytics engineers the flexibility to organize models by domain or environment. The tags configuration is also valid under models: and is widely used to group models logically for selection, documentation, or orchestration workflows.
Option B (source) is incorrect because sources are defined under YAML files in the sources: section, not under models: in dbt_project.yml. Option D (test) is incorrect because tests must be defined in model or source YAML files, not inside the project configuration. Option E (target) is not a configuration that applies to models; rather, it refers to dbt runtime environments and cannot be configured under the models: block.
dbt's project configuration system ensures that model-level behavior is managed centrally and consistently, and schema and tags are two of the officially supported configuration keys under models:.
NEW QUESTION # 321
While onboarding a new team member, you need to ensure consistency between their local development setup and your existing production dbt deployment. Which of these are essential?
Answer: D
Explanation:
A: Version control and pinning dependencies ensure reliable behavior across machines. B: Accurate profiles are vital for successful dbt runs_ C: Data warehouse access is necessary for the developer to function.
NEW QUESTION # 322
Your development environment uses a smaller, sampled dataset compared to production for efficiency. When a new performance-sensitive model is deployed, users report significant slowdowns. What might be some of the potential causes?
Answer: A
Explanation:
A: Sampled data obscures performance problems related to data volume. B: Optimizations designed for small data might not be effective at scale. C: Differences between environments can drastically affect performance.
NEW QUESTION # 323
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?
Answer: D
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 # 324
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