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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Objectives
Analytics Engineering Foundations	- Modern data stack concepts (ELT vs ETL) 1. Role of dbt in analytics engineering 2. Warehouse-centric transformation workflows - SQL proficiency for analytics 1. Data modeling in SQL 2. Joins, aggregations, and window functions
Documentation and Lineage	- dbt documentation system 1. Model descriptions and metadata 2. Auto-generated docs site - Data lineage understanding 1. Directed acyclic graph (DAG) 2. Dependency tracking with ref()
Deployment and Orchestration	- Environments and workflows 1. Version control with Git 2. Development vs production environments - Running dbt in production 1. dbt Cloud and job scheduling 2. CI/CD integration patterns
dbt Core Concepts	- Project structure and configuration 1. dbt_project.yml configuration 2. Packages and dependencies - Models and materializations 1. Views, tables, incremental models 2. Ref and source functions
Testing and Data Quality	- Data validation strategies 1. CI-based validation workflows 2. Schema testing practices - Built-in and custom tests 1. Custom SQL tests 2. Generic tests (unique, not null, relationships)

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q22-Q27):

NEW QUESTION # 22
You create tests to validate counts and timestamps against a baseline dataset. The tests fail unexpectedly. What might be possible root causes?

A. The baseline dataset itself has become corrupted
B. There are differences in data types or time zone handling between the model and baseline.
C. Your tests are too strict and need more generous tolerances.
D. Your upstream ETL process has a logic error, leading to incorrect data.

Answer: A,B,C,D

Explanation:
Each scenario could cause a baseline comparison test to fail, covering issues in the data pipeline, the baseline, and the test logic itself.

NEW QUESTION # 23
"The compiled SQL looks correct, but I'm still getting wrong results in my model!" What might you suggest to a colleague having this issue?

A. Review the logic in 'on-run-start' or 'on-run-end' hooks, as they could be modifying data-
B. Examine the source tables for data quality issues like duplicates or missing values.
C. All of the above.
D. Test the model in isolation using the dbt run -select flag to narrow down dependencies.

Answer: C

Explanation:
Sometimes, even with correct SQL, the issue can lie in data itself, external interactions, or hidden dependency effects.

NEW QUESTION # 24
You run the command:
dbt test --select 'test_type:singular'
What will the command run?
Options shown:

A. furniture_customers_test
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
stg_tpch_orders_assert_positive_price
Choose 1 option.

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 # 25
You're refactoring a project with long model files containing intertwined logic. Which of the following is NOT a typical sign of a good candidate for applying modularity principles?

A. The same SQL patterns are repeated with minor variations.
B. Renaming code blocks would improve readability.
C. Portions of the logic form distinct conceptual steps in the transformation process.
D. The models are relatively small and perform simple transformations.

Answer: D

Explanation:
Small and simple models might already be sufficiently modular. The other options signal that refactoring into reusable components would be beneficial.

NEW QUESTION # 26
While onboarding a new team member, you need to ensure consistency between their local development setup and your existing production dbt deployment. Which of these are essential?

A. Setting up access and permissions in the data warehouse for the new user, aligning with your team's security practices.
B. Enforcing version control and utilizing a requirements txt file to pin dbt and adapter dependencies.
C. All of the above.
D. Providing clear documentation on configuration of profiles_yml to connect to the correct targets.

Answer: C

Explanation:
A: Version control and pinning dependencies ensure reliable behavior across machines. B: Accurate profiles are vital for successful dbt runs_ C: Data warehouse access is necessary for the developer to function.

NEW QUESTION # 27
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