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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q222-Q227):

NEW QUESTION # 222
Your team sometimes defines raw data sources directly in dbt models using .yml files within the models directory. When might this approach be problematic?

A. If the raw dataset's schema is subject to change.
B. If the raw dataset requires complex transformations.
C. If multiple models utilize the same raw dataset.
D. If the raw dataset is accessed via a non-standard data warehouse connector.

Answer: C

Explanation:
Defining raw sources within models leads to duplication and potential maintenance issues when multiple models share that dependency. A separate sources.yml file is generally preferred for shared datasets.

NEW QUESTION # 223
Your company wants to standardize pull request templates. Which information would be beneficial to include in such a template?

A. All of the above.
B. Specific instructions for the reviewer, if certain aspects need special attention.
C. A section to link to relevant design documents or specifications.
D. Checkboxes for confirming that tests have been run and documentation has been updated if necessary.

Answer: A

Explanation:
A: Checklists ensure core quality steps are followed. B: Linking design documents provides context for reviewers. C: Guidance helps reviewers focus their feedback.

NEW QUESTION # 224
Which is true about writing generic tests?
Choose 1 option.

A. They must contain a {{ ref() }} snippet to a model.
B. They should accept one or both of these arguments: model and column_name.
C. They do not need to be specified under a model's YAML configurations.
D. They are written using the {% macro %} wrapper.
E. They should always accept a column_name.

Answer: D

Explanation:
The correct answer is E: They are written using the {% macro %} wrapper.
Generic tests in dbt are implemented as macros, which means they must be defined using the {% macro %} Jinja syntax. These macros return a SQL query that evaluates to rows representing test failures. dbt executes these queries and marks the test as failed if any rows are returned. This requirement is explicitly documented:
all generic tests are macros located in a test directory or within a package.
Option A is partially correct but not universal. Generic tests typically accept arguments such as model or column_name, but dbt does not require both or either. Custom tests can accept any parameters defined by the user. Option B is incorrect because tests do not require ref(); dbt injects the model relation for you when the test is executed. Option C is false because generic tests must be declared in YAML under a model or source for dbt to run them. Option D is incorrect because tests do not always need a column_name (e.g., relationship tests, row-count tests, table-level validations).
Therefore, the defining and universally required characteristic is that generic tests are written as macros, making E the correct answer.

NEW QUESTION # 225
Your dbt project contains models that process data with varying levels of sensitivity. Which of the following might be reasons to utilize different schemas or even different targets within your data warehouse for these data sensitivity levels?

A. To optimize query performance, as certain models might benefit from specific data warehouse configurations based on their workload.
B. To comply with data governance regulations that mandate separation of different data types.
C. All of the above-
D. To implement stricter access controls limiting which users or roles can interact with sensitive data-

Answer: C

Explanation:
A: Separate schemas or targets enhance access control granularity. B: Some data workloads might have different performance requirements- C: Compliance often necessitates structured data organization-

NEW QUESTION # 226
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'"
D. tests:
- not_null:
- config:
where: "state = 'completed'"
Choose 1 option.

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 # 227
......

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