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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q232-Q237):

NEW QUESTION # 232
You're working in a highly regulated environment. Merges into the main branch require multiple approvals. Which additional steps might need to be incorporated into your merge process?

A. Link pull requests to detailed change documentation and impact analysis.
B. All of the above
C. Use a protected branch workflow on the remote repository with required reviews.
D. Utilize signed commits to add a layer of traceability and verification-

Answer: B

Explanation:
A: Clear documentation is essential for compliance and audit trails. B: Protected branches enforce the approval process at the repository level. C: Signed commits offer proof of authorship and agreement on the changes-

NEW QUESTION # 233
(Multiple Select)

A. Configuring tests to run only on models that have changed or have upstream changes.
B. Running dbt tests in parallel with dbt model builds whenever possible-
C. Scheduling less critical tests to run during off-peak hours.
D. Designing tests, where feasible, to examine subsets of data rather than full tables.

Answer: A,C,D

Explanation:
A targets tests to the most relevant areas, reducing workload. C leverages less busy periods to avoid resource contention. D reduces individual test runtimes through sampling. B is generally inadvisable, as testing and model building might compete for resources.

NEW QUESTION # 234
Which two configuration items can be defined under models: in your dbt_project.yml file?
Choose 2 options.

A. test
B. tags
C. schema
D. target
E. source

Answer: B,C

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 # 235
A sudden data quality issue occurs in production. You need to quickly reproduce the problem in a lower environment but retain a point-in-time snapshot of production dat a. Which strategies might you employ? Create a backup of the production database and restore it to a separate development or testing database.

A. Utilize data replication features (if supported by your data warehouse) to create a near real-time mirror of production data in a
B. A combination of the above, depending on time constraints and available resources.
C. Use dbt snapshots to capture critical production tables during a defined timeframe for later use in troubleshooting.
D. staging area.

Answer: B

Explanation:
A: Backups offer static point-in-time snapshots. B: Replication might be ideal for immediate mirroring, if available. C: Snapshots are lightweight yet can be time-sensitive.

NEW QUESTION # 236
You're considering using dbt's --store-failures flag when running tests. Which of the following are potential implications of using this flag?

A. This flag alters how dbt calculates test results
B. Successful models will not be rebuilt if downstream dbt tests are marked as failures.
C. Troublesl-ming failing tests will become easier, as data related to the failure is persisted.
D. The overall dbt test command may run faster-

Answer: C

Explanation:
A is the primary purpose of -store-failures. B is not how dependencies work in dbt. C is unlikely as additional data storage is involved. D is not the case; it influences preservation of data associated with the test, not its logic.

NEW QUESTION # 237
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