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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q303-Q308):

NEW QUESTION # 303
You want to experiment with a new column in an existing model without risking production changes. Which configuration strategy in your dbt_project.yml would support this safely?

A. Define separate configurations for the column under the model and use the enabled property.
B. Utilize git branches and have different dbt_project.yml files for your production and experimental branches.
C. Modify the model SQL using the config.get() macro to dynamically control the column's behavior
D. Add a -select flag when using dbt run to execute only the modified model.

Answer: A

Explanation:
Model configurations with the enabled property offer a structured way to experiment within the project file.

NEW QUESTION # 304
You run the command:
dbt test --select 'test_type:singular'
What will the command run?
Options shown:

A. furniture_customers_test
stg_tpch_orders_assert_positive_price
Choose 1 option.
B. macro_stg_tpch_orders_assert_pos_price
macro_stg_tpch_suppliers_assert_pos_acct_bal
stg_tpch_orders_assert_positive_price
C. furniture_customers_test
macro_stg_tpch_orders_assert_pos_price
macro_stg_tpch_suppliers_assert_pos_acct_bal
stg_tpch_orders_assert_positive_price
D. furniture_customers_test

Answer: B

Explanation:
In dbt, singular tests are custom SQL tests that live as standalone .sql files inside the root /tests directory, not inside /tests/generic. A singular test returns rows that indicate failure, and dbt runs the SQL directly as written. Generic tests, on the other hand, live inside the /tests/generic folder and are YAML-based macro- driven tests.
From your test folder structure (shown in the original screenshot), the following SQL files exist:
Inside /tests/generic/
* furniture_customers_test.sqlThis file is a generic test, not singular.
Inside the root /tests directory:
* macro_stg_tpch_orders_assert_pos_price.sql
* macro_stg_tpch_suppliers_assert_pos_acct_bal.sql
* stg_tpch_orders_assert_positive_price.sql
These are singular tests, because they are standalone SQL files in the tests root folder.
When you run:
dbt test --select 'test_type:singular'
dbt filters for only tests classified as singular. It ignores generic tests entirely.
Therefore, only the following 3 tests will run:
* macro_stg_tpch_orders_assert_pos_price
* macro_stg_tpch_suppliers_assert_pos_acct_bal
* stg_tpch_orders_assert_positive_price
This matches Option C, making it the correct answer.

NEW QUESTION # 305
Your stakeholders require robust data visualization and dashboarding capabilities beyond what dbt itself offers. Which of the following would be good pairings with dbt to address this need?

A. Spreadsheet software (like Excel or Google Sheets)
B. Data observability platforms
C. Version control systems (e.g., Git)
D. Modern Bl tools (like Tableau, Looker, Power Bl)

Answer: D

Explanation:
Modern Bl tools specialize in taking transformed data from dbt and creating rich, interactive visualizations and dashboards for end-users. The other options have their places in the data stack, but not for primary dashboarding.

NEW QUESTION # 306
(Multiple Select)

A. A critical upstream data source has been delayed, and you only want to refresh dependent models once the data arrives.
B. You need to temporarily disable a computationally expensive model that isnt critical for daily reporting.
C. There's an urgent request to update a single dashboard, and you know the exact subset of models to re-run.
D. You've refactored a core model and need to quickly validate its output and downstream dependencies.

Answer: A,C,D

Explanation:
Each involves a need for targeted, not blanket, execution. D is more about configuration than selective runs.

NEW QUESTION # 307
You have an urgent hotfix that needs to be deployed while a larger feature branch is still under review. Which strategies could you consider?

A. Create a dedicated branch from the main branch specifically for the hotfix.
B. Merge the hotfix into the feature branch and wait for the entire feature to be approved.
C. Merge the hotfix into the main branch and then rebase the feature branch on top of the new main branch.
D. Temporarily revert the feature branch changes, deploy the hotfix, and then restore the feature branch.

Answer: A,C

Explanation:
B: A dedicated hotfix branch isolates changes and provides the quickest path to deployment. D: Rebasing the feature branch after the hotfix ensures it includes the necessary fix.

NEW QUESTION # 308
......

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