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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q276-Q281):

NEW QUESTION # 276
You're tasked with creating a model for audit purposes. The data must be preserved exactly as it was at a specific point in time. Update frequency is low, and there's no need for additional transformations on the captured dat a. What materialization should you use?

A. View
B. Snapshot
C. Table
D. Incremental

Answer: B

Explanation:
Snapshots are designed for historical preservation. They capture the state of a source at a moment in time, providing a perfect audit trail.

NEW QUESTION # 277
You've made several commits to your feature branch. Before merging into the main branch, you want to consolidate the changes into a single, clear commit. What Git technique would help achieve this?

A. Manually copy your files into a new branch, commit, and issue a pull request.
B. Run git rebase main followed by git commit -amend.
C. Use git rebase -i (interactive rebase) to squash commits together.
D. git cherry-pick specific commits from your branch and reapply them.

Answer: C

Explanation:
Interactive rebasing (git rebase -i) provides fine-grained control to squash, edit, or rearrange commits, creating a cleaner commit history

NEW QUESTION # 278
16. Your tests folder looks like:
tests
### generic
### furniture_customers_test.sql
macro_stg_tpch_orders_assert_pos_price.sql
macro_stg_tpch_suppliers_assert_pos_acct_bal.sql
stg_tpch_orders_assert_positive_price.sql
You run the command:
dbt test --select 'test_type:singular'
What will the command run?
Options from screenshot:

A. macro_stg_tpch_orders_assert_pos_price
macro_stg_tpch_suppliers_assert_pos_acct_bal
stg_tpch_orders_assert_positive_price
B. furniture_customers_test
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

Answer: A

Explanation:
In dbt, a singular test is any SQL file placed directly inside the tests/ directory-not inside the tests/generic/ folder. Singular tests contain a custom SQL query where returning any rows means failure. They are distinct from generic tests, which are YAML-defined and live inside the generic directory, often referencing macros.
Looking at the folder structure:
In tests/generic/
* furniture_customers_test.sql # This is a generic test, not a singular test.
In the root tests/ directory
* macro_stg_tpch_orders_assert_pos_price.sql # singular test
* macro_stg_tpch_suppliers_assert_pos_acct_bal.sql # singular test
* stg_tpch_orders_assert_positive_price.sql # singular test
When you run:
dbt test --select 'test_type:singular'
dbt selects only singular tests, meaning tests that are individually written SQL files in the top-level tests/ directory.
Therefore, dbt will run:
* macro_stg_tpch_orders_assert_pos_price
* macro_stg_tpch_suppliers_assert_pos_acct_bal
* stg_tpch_orders_assert_positive_price
It will not run furniture_customers_test, because that file is inside tests/generic/, which is reserved for template-based generic tests and is not classified as singular.
Thus, the correct answer is Option C.

NEW QUESTION # 279
(Multiple Select)

A. If macros reference raw tables, those dependencies might not be reflected in dbt's lineage graphs.
B. Macros can completely obfuscate dependencies, making them untraceable.
C. Macros generally make dependency tracking easier by encapsulating logic.
D. If macros themselves have dependencies on other macros, this adds an extra layer to consider.

Answer: A,D

Explanation:
Macros can introduce "hidden" dependencies. Also, if your macros build upon each other, you must track their internal dependencies as well.

NEW QUESTION # 280
A team member proposes directly joining multiple raw source tables into a single large model for convenience.
Which of the following is a potential long-term consequence of this approach?

A. Your DAG might inadvertently develop circular dependencies.
B. Maintenance complexity increases as business logic or source tables change.
C. Incremental materialization strategies would no longer be applicable.
D. The dbt test command might run slower due to the complex join logic.

Answer: B

Explanation:
Directly joining raw sources sacrifices modularity and flexibility. While option A is partially true, B highlights a more significant maintainability risk.

NEW QUESTION # 281
......

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