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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q35-Q40):

NEW QUESTION # 35
Your team decides to use separate schemas for development and production within the same data warehouse. Which of the following dbt features are essential for managing this workflow effectively?

A. Macros and Jinja templating to dynamically switch target schemas.
B. dbt snapshots to compare data state between environments-
C. dbt seeds to populate test data in your development schema.
D. Environment variables to store environment-specific configurations.

Answer: A,D

Explanation:
A makes code portable across environments. D allows for environment-specific settings. B is useful, but not specific to multi-schema setups C is important for testing, but not the core deployment environment distinction.

NEW QUESTION # 36
In what situations might it be acceptable to use raw data directly for reporting or analytics purposes?

A. In environments where strict data governance and transformation processes are in place.
B. Generally, using raw data directly for reporting should be avoided due to potential quality and consistency issues.
C. When performance is a top priority, and the overhead of additional data transformations is undesirable.
D. When dealing with simple analyses, and there's high confidence in the quality of the raw data source.

Answer: B

Explanation:
Raw data is often unpredictable- However, under specific conditions like those listed in A, B, or C, it could be considered if the risks and trade-offs are well understood.

NEW QUESTION # 37
You've updated a model's description in a YAML file to reflect a new business requirement. You've also added additional context to the column descriptions. After regenerating the documentation, you notice the model description has updated, but the column descriptions have not. What could be the most likely reasons?

A. You forgot to run dbt docs generate after modifying the YAML file.
B. The documentation was not configured correctly to display column descriptions.
C. The model's YAML file has incorrect syntax preventing column descriptions from rendering.
D. You are viewing an older cached version of the documentatiom

Answer: A,D

Explanation:
Explanation: B:
The dbt docs generate command is essential for updating the documentation website with changes made in the project files. D: Web browsers often cache content; you might need to clear your cache or force a refresh to see the latest changes.

NEW QUESTION # 38
You have created a model called stg_tasks and now you need to implement tests.
You provide this in schema.yml:
version: 2
models:
- name: stg_tasks
columns:
- name: completed_at
tests:
- not_null:
- config:
where: "state = 'completed'"
You receive this compilation error:
[WARNING]: Did not find matching node for patch with name 'stg_tasks' in the 'models' section of file
'models/example/schema.yml'
How can you change the configuration on the not_null test to fix this compiler error?

A. tests:
- not_null:
- config:
where: "state = 'completed'"
B. tests:
- not_null:
config:
where: "state = 'completed'"
C. tests:
- not_null:
- config:
where: "state = 'completed'"
Choose 1 option.
D. tests:
- not_null:
config:
where: "state = 'completed'"

Answer: B

Explanation:
In dbt, when you configure a generic test like not_null in YAML, the configuration for that test must be a mapping, not another list item. The correct structure is:
tests:
- not_null:
config:
where: "state = 'completed'"
In your original YAML, you wrote:
tests:
- not_null:
- config:
where: "state = 'completed'"
The extra dash (- config) makes config an element of a list rather than a key under the not_null test. This breaks the expected shape of the test definition. When dbt parses the schema.yml, it fails to correctly interpret the patch for the stg_tasks model, which leads to the warning: "Did not find matching node for patch with name 'stg_tasks'...".
By removing the extra dash and nesting config directly under not_null, dbt now reads this as a single generic test named not_null with a config block that passes the where argument. This allows dbt to correctly attach the test to the completed_at column of the stg_tasks model and eliminates the compiler warning.
Therefore, Option B is the only structurally valid configuration and is the correct answer.

NEW QUESTION # 39
(Multiple Select)

A. Tables generally offer the fastest query performance for pre-computed models.
B. Tables are well-suited for datasets that undergo frequent, wholesale changes.
C. Tables, by default, are rebuilt completely with each dbt run.
D. Tables persist their results on disk, consuming storage resources.

Answer: A,D

Explanation:
Tables trade off storage for excellent query performance and are a good fit for stable datasets or ones that can be efficiently updated.

NEW QUESTION # 40
......

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