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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q317-Q322):

NEW QUESTION # 317
You're working in a highly collaborative environment. How could you manage contributions and updates to complex lineage macros to ensure maintainability and prevent conflicts?

A. Utilize a robust version control system (e.g., Git) for macro code.
B. All of the above-
C. Establish coding style guides and peer-review processes specifically for macros.
D. Limit the number of people authorized to make changes to sensitive lineage macros-

Answer: B

Explanation:
A Version control is essential for tracking changes and collaboratiom B: Style guides and reviews improve code quality and reduce errors. C: Controlled access can be important, while still allowing for collaboration through review processes.

NEW QUESTION # 318
Your dbt project pulls data from a SaaS application using a third-party adapter. You observe performance issues. Where might you start optimizing?

A. Configure the source as an incremental materialization within your project file.
B. Check your dbt_project.yml for project-level performance settings.
C. Investigate the third-party adapter's settings or documentation for potential bottlenecks.
D. Review the source definitions to see if unnecessary data is being selected.

Answer: C

Explanation:
Third-party adapters often introduce bottlenecks. Start with optimizing whats specific to the adapter The others might help in some cases but are less directly dependent on the external data source.

NEW QUESTION # 319
Which statement is true regarding source freshness checks?
Choose 1 option.

A. dbt build will automatically run source freshness checks.
B. dbt source freshness should always be the final command in a run.
C. The freshness check can be disabled with freshness: null.
D. A source freshness check will always exit immediately after the first failure.

Answer: C

Explanation:
The correct answer is A: The freshness check can be disabled with freshness: null.
In dbt, freshness checks are controlled by the freshness configuration block within a source definition. If a project includes a default freshness configuration, but you want to turn off freshness checking for a specific table, you can explicitly set freshness: null. This overrides inherited settings and tells dbt not to compute or evaluate freshness for that object.
Option B is incorrect because dbt evaluates all configured sources before finishing; it does not exit after the first failure. Instead, it completes the run and reports pass/warn/error statuses according to the configured thresholds.
Option C is incorrect because the placement of freshness checks is flexible. Some teams run dbt source freshness first to validate data arrival before running models; others run it separately or at the end of a workflow. There is no requirement that it always be last.
Option D is incorrect because dbt build does not automatically run freshness checks. Freshness checks are performed only when dbt source freshness is executed explicitly or configured in a dbt Cloud job step.
Therefore, A is the only statement that correctly describes the behavior of source freshness checks.

NEW QUESTION # 320
(Multiple Select)

A. The source data is sensitive and requires role-based access control.
B. You need to apply custom column-level transformations to a raw source.
C. The source has multiple tables with related schemas requiring standardization.
D. You want to test different loading strategies for a large source table.

Answer: B,C

Explanation:
yml files allow for complex source schemas and column transformations. Access control and loading strategies are usually handled at the database or project-level configuration.

NEW QUESTION # 321
You introduce a minor formatting change to a large SQL model. Afterwards, the results change unexpectedly. Which dbt-related issue might explain this, even if the SQL itself appears correct?

A. You've used a reserved keyword as a column alias without properly quoting it.
B. A subtle indentation change in a CTE accidentally modifies the execution order within the query.
C. An upstream data issue only surfaces due to the formatting change making that part of the query execute differently.
D. There's a version mismatch between the dbt library used during development and in production.

Answer: B

Explanation:
Whitespace matters in SQL, and CTE order is often significant even if the query might still be validly formatted.

NEW QUESTION # 322
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