Types Of dbt Labs dbt-Analytics-Engineering Exam Practice Test Questions

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
Deployment and Orchestration	15%	- Git version control integration - Environments (dev, staging, prod) - Jobs and scheduling in dbt Cloud - CI/CD with dbt Cloud
Data Transformation Techniques	25%	- Jinja templating - Macros and packages - Refactoring and incremental models - Common table expressions and subqueries
Models	25%	- Materializations (table, view, ephemeral, incremental) - Sources and references - Snapshots - Seeds - Writing and managing SQL models
dbt Fundamentals	15%	- dbt workflow and best practices - dbt Core vs dbt Cloud - dbt project structure
Testing and Documentation	20%	- dbt docs and DAG visualization - Documentation generation - Custom data tests - Schema tests (unique, not_null, accepted_values, relationships)

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q29-Q34):

NEW QUESTION # 29
The dataset raw user activity is critical to several models. You've been informed that a major schema change is scheduled for this source. Select the best way to proactively mitigate the potential impact of this change on your dbt project.

A. Run dbt test after the schema changes and address any failures.
B. Communicate with the relevant data team to create a temporary staging table mirroring the old schema.
C. Pause all dbt jobs until the schema change risk is fully assessed.
D. Create custom data tests that validate the critical columns in raw_user_activity.

Answer: D

Explanation:
Custom data tests proactively ensure that even if the schema changes, the critical data in raw_user_activity remains valid and consistent for your models. Other options are reactive or might introduce unnecessary downtime.

NEW QUESTION # 30
You're getting inconsistent errors when adding new models in your dbt_project.yml. You suspect typos or indentation issues. How can you proactively improve this situation?

A. Use a code editor or IDE with YAML-specific linting and auto-formatting support.
B. All of the above.
C. Set up a pre-commit hook that runs a YAML validation script before committing changes.
D. Write tests covering various aspects of dbt_project.yml to proactively catch errors.

Answer: B

Explanation:
Each of these plays a role in preventing YAML errors.

NEW QUESTION # 31
You frequently need to spin up short-lived development environments on demand for testing and experimentation. Which dbt feature would streamline this process, especially when it involves custom configuration?

A. Using dbt tags to selectively execute parts of your project.
B. Creating multiple deployment environments in dbt Cloud.
C. dbt's -vars flag to override variable values.
D. dbt profiles defined in your dbt_project.yml file.

Answer: C,D

Explanation:
A encapsulates environment settings in reusable blocks- B allows for ad-hoc adjustments when running dbt- C is relevant for cloud-based setups, but less flexible for on-the-fly changes- D relates to model selection, not environment setup.

NEW QUESTION # 32
dbt Model Snippet:SQL

A. There's a custom macro in use that dynamically changes schemas.
B. Your dbt_projectyml file has a model-level schema override.
C. The stg_orders model uses a schema config in its own model SQL
D. Your sources.yml file is not configured correctly-

Answer: B

Explanation:
Model-level schema configurations override other settings. Check your project file for this model. The others are possible but less common patterns

NEW QUESTION # 33
Your team establishes a policy for handling different levels of test failures (e.g., warnings vs. critical errors). How could you implement this policy effectively within your dbt workflows?

A. Use custom severity levels in your test definitions and a post-hook to manage actions accordingly.
B. Run dbt test multiple times with varying filters based on desired severity levels.
C. Rely on your data observability platform to differentiate and alert based on dbt test results.
D. Use dbt tags for classifying tests, then selectively execute them.

Answer: A,C,D

Explanation:
Each provides a mechanism to act upon varying severity levelsA leverages dbt's built-in features- C integrates with external monitoring tools. D offers flexible execution control.

NEW QUESTION # 34
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