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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 36

You have a dbt project with models defined as views. After deploying to a production database, the view objects are present, but no data is displayed when querying them. What might be the root cause?

Correct Answer: B
B is a common security-related cause of 'missing' data. The others are less likely; views, logs, and dbt core logic tend to be consistent.
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Question 37

Your company wants to standardize pull request templates. Which information would be beneficial to include in such a template?

Correct Answer: D
A: Checklists ensure core quality steps are followed. B: Linking design documents provides context for reviewers. C: Guidance helps reviewers focus their feedback.
insert code

Question 38

(Multiple Select)

Correct Answer: A,B,C
These involve domain-specific logic or cross-table checks, which are not covered by standard generic tests. D (column order) is typically less critical for analysis purposes.
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Question 39

Correct Answer:

Explanation:
Information Type
Retrieved From
Singular tests
.sql files
Column data types
Data platform information schema
Generic tests
.yml configuration
SQL code
C. .sql files
Column descriptions
.yml configuration
Model dependencies
.sql files
The dbt docs command compiles metadata about your project by gathering information from three primary sources: your warehouse's information schema, your YAML configuration files, and your SQL model files. Understanding which metadata comes from which source is essential for debugging and for effective documentation practices.
Singular tests live inside .sql files within the /tests directory. Since dbt renders these tests directly from SQL files, their definitions appear in documentation sourced from that location.
Column data types come from the warehouse itself. dbt introspects the data platform information schema to retrieve actual types because dbt does not infer or define column types-only the warehouse does.
Generic tests (e.g., unique, not_null, accepted_values) are declared in .yml files. These YAML definitions contain test configurations, descriptions, and parameters, which dbt uses to document and execute these tests.
SQL code for models is naturally sourced from .sql files where the models are defined. This includes logic such as SELECT statements, CTEs, and transformations.
Column descriptions are written exclusively in .yml files. dbt never extracts descriptions from SQL comments-only from YAML.
Model dependencies come from the ref() and source() calls inside .sql model files, which dbt parses to build the DAG.
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Question 40

Several of your users report that dashboards built on top of your dbt models are intermittently displaying stale dat a. Which of the following might be a potential cause?

Correct Answer: D
Each of these could lead to stale data Start by examining freshness checks, then materializations, and if those are correct, inspect the DAG for execution bottlenecks.
insert code
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