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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
Models	25%	- Seeds - Writing and managing SQL models - Materializations (table, view, ephemeral, incremental) - Snapshots - Sources and references
Testing and Documentation	20%	- Schema tests (unique, not_null, accepted_values, relationships) - Custom data tests - dbt docs and DAG visualization - Documentation generation
Deployment and Orchestration	15%	- Jobs and scheduling in dbt Cloud - Git version control integration - Environments (dev, staging, prod) - CI/CD with dbt Cloud
Data Transformation Techniques	25%	- Jinja templating - Common table expressions and subqueries - Refactoring and incremental models - Macros and packages
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 (Q46-Q51):

NEW QUESTION # 46
You're setting up CI/CD for your dbt project to automate deployments. Which aspects of your testing strategy might need adaptation for a production-focused CI/CD workflow?

A. Prioritizing tests with strict thresholds to avoid false positives from minor data variations in production.
B. Emphasizing tests with longer run times for thorough checks before deployment.
C. Including smoke tests that run in production to verify core functionality after a deployment.
D. Disabling all tests that rely on creating new tables, to avoid impacting the production database.

Answer: A,C

Explanation:
B ensures the deployed changes actually work in the real environment. C helps maintain CI/CD flow without unnecessary disruptions. A is counterproductive in a time-sensitive CI/CD context. D would overly limit your testing coverage.

NEW QUESTION # 47
You typically use dbt run to execute your project. However, you want to trigger a refresh of only models that depend on newly updated source dat a. How could you achieve this?

A. Leverage dbt snapshots to identify changed sources and derive the dependent model list.
B. Manually determine dependent models, then use dbt run -m
C. Add dbt run to the post-hook of your upstream ETL process, so it triggers upon data arrival.
D. Configure your sources with the freshness property and run dbt source freshness.

Answer: A,D

Explanation:
B automates discovery of what's stale. D uses snapshots for the same purpose. A is tedious, C runs all models, not selectively

NEW QUESTION # 48
You wrote this test against your fct_orders model to confirm status filters were properly applied by a parent model:
{{
config(
enabled=true,
severity='error'
)
}}
select *
from {{ ref('fct_orders') }}
where status_code = 13
Which statement about this test is true?

A. The file must be saved in the tests/generic directory.
B. Records with status_code = 13 will cause this test to fail.
C. This test will warn instead of erroring when you use the --warn-error flag.
D. You must attach the test to the model in orders.yml for it to run.

Answer: B

Explanation:
This test is a singular test, meaning it is defined as a standalone SQL file placed inside the /tests directory (not attached through YAML like generic tests). dbt executes singular tests by running the SQL query, and the test fails if the query returns any rows. In this case, the test selects all records from fct_orders where status_code = 13. That means if even one row in fct_orders has a status code of 13, the test will fail, because dbt interprets returned rows as evidence of a data-quality issue.
The configuration block at the top sets severity='error', meaning the test raises an error when it fails, rather than a warning. This setting overrides default severity behavior, so option B is incorrect. Singular tests do not need to be attached in YAML because they run automatically when placed under /tests # making option A incorrect. Meanwhile, generic tests live in /tests/generic, but singular tests should live directly under /tests (option C incorrect).
Therefore, the only correct statement is that records with status_code = 13 will cause the test to fail, because the test query is explicitly written to identify such rows.

NEW QUESTION # 49
You're setting up a CI/CD pipeline for dbt deployments. Which actions can help maintain data integrity and consistency between your development, staging, and production environments?

A. Enforce a branching strategy that mirrors environment progression (e.g., dev branch deploys to dev, etc. )
B. Utilize dbt logs and artifacts to track any changes made outside the standard deployment pipeline in each environment.
C. All of the above.
D. Implement automated tests that validate data quality and model assumptions across all environments.

Answer: C

Explanation:
A: Tests ensure consistent behavior and catch issues early across environments. B: Structured branching aligns code changes to the environments they affect. C: Tracking unexpected changes is vital for auditing and troubleshooting.

NEW QUESTION # 50
You define a source and later try to reference it. Compilation fails with: "Model depends on a node named 'my source' which was not found". What are some likely causes?

A. Your dbt_project.yml configuration has the incorrect source-paths setting.
B. There's a typo in how you're referencing the source name using source().
C. The source definition is missing or incorrect in your dbt_project.yml or sources file.
D. All of the above.

Answer: D

Explanation:
Dependency issues can manifest like this. Check your source configuration, the source() usage, and even your project's file paths.

NEW QUESTION # 51
......

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