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  1. Home
  2. dbt Labs Certification
  3. dbt-Analytics-Engineering Exam
  4. dbtLabs.dbt-Analytics-Engineering.v2026-11-13.q153 Dumps
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Question 116

13. An analyst on your team has informed you that the business logic creating the is_active column of your stg_users model is incorrect.
You update the column logic to:
case
when state = 'Active'
then true
else false
end as is_active
Which test can you add on the state column to support your expectations of the source data? Choose 1 option.

Correct Answer: A
The purpose of this question is to determine how to validate that the input values in the state column support the business logic that determines the is_active field. Since the logic checks whether state = 'Active', it is critical that the state column only contains values that the business process expects. In the example shown, acceptable states appear to be: 'active', 'churned', and 'trial'.
The correct way to enforce this expectation is to apply an accepted_values test on the state column. This ensures that any unexpected state (e.g., 'inactive', 'pending', 'deleted', or NULL) will cause the test to fail, alerting the team that the upstream system is producing unexpected or invalid values. Additionally, adding not_null ensures every user record contains a valid state.
Option A is the only configuration that applies the accepted values test to the correct column (state) and reflects the expected domain of values.
Options B and D incorrectly apply tests to the derived column is_active, not the source column that needs validation. Option C only checks nullability and uniqueness, which does not validate the range of allowed values and thus does not protect the business logic.
Therefore, Option A is the only correct answer.
insert code

Question 117

Your dbt project is part of a larger application where code for multiple components is merged into a shared main branch. Conflicts are becoming frequent. Which strategies could help mitigate merge conflicts?

Correct Answer: D
Explanation: A Clear ownership reduces the likelihood of conflicting edits. B: Proactive communication helps avoid surprise changes that can cause conflicts_ C: Smaller changesets decrease the potential for conflicting changes across branches.
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Question 118

Which two code snippets result in a lineage line being shown in the DAG? Choose 2 options.

Correct Answer: A,B
In dbt, the Directed Acyclic Graph (DAG) is created from model dependencies, which dbt identifies only through two mechanisms: the ref() function for referencing dbt models and the source() function for referencing declared sources. These functions are explicitly designed to tell dbt how models relate to each other so that dbt can track lineage, enforce build order, and generate documentation.
Option A, {{ source('source', 'table') }}, correctly references a declared source. Any model using source() establishes an upstream dependency on that source table. dbt will therefore draw a lineage line in the DAG from the source to the model.
Option B, {{ ref('stg_jaffle_shop__customers') }}, is the canonical way to reference another dbt model. ref() ensures dbt determines dependencies at compile time, and thus creates a DAG edge between this model and its parent.
The remaining options do not create lineage:
* C directly references a database object, which dbt cannot interpret as a dependency.
* D uses a Jinja variable unrelated to lineage.
* E is invalid, because source() requires two arguments: a source name and table name, not a dotted string.
Therefore, A and B are the only valid answers.
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Question 119

Which explanation describes how dbt infers dependencies between models?
Choose 1 option.

Correct Answer: A
The correct answer is A: Information is gathered from the use of source and ref macros.
dbt determines the dependency graph - the DAG - by analyzing calls to ref() and source() inside model SQL files. These macros explicitly declare relationships between models. When a developer writes ref ('orders'), dbt interprets this as: "the current model depends on the orders model." Similarly, source() indicates dependencies on upstream raw data sources. This declarative approach allows dbt to build a structured and deterministic DAG without scanning SQL for implicit table references.
Option B is incorrect because dbt does not query database objects to infer dependencies; it resolves dependencies at compile time through metadata generated from model files. Option C is incorrect because dbt intentionally does not parse SQL to detect table names-this would be brittle and error-prone across warehouses. Instead, dbt requires explicit references to maintain reliability. Option D is incorrect because YAML files define metadata about models and sources but do not create dependency relationships between them.
Thus, the dependency graph is built exclusively by reading ref() and source() macro calls, which ensures clarity, correctness, and maintainability within the analytics engineering workflow.
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Question 120

(Multiple Select)

Correct Answer: A,B
Compiled SQL helps verify applied logic and is useful for query optimization. Line numbers in errors often point to compiled SQL- Data type errors are typically less related to the compiled structure.
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