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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q352-Q357):

NEW QUESTION # 352
You need a materialization that automatically adapts to upstream schema changes while still preserving query performance. Which dbt materialization offers this kind of flexibility?

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

Answer: A

Explanation:
Views are dynamically built at query time, inheriting their schema from the underlying sources, thus providing built-in adaptation.

NEW QUESTION # 353
In development, you want to avoid having to re-run all upstream models when refactoring part of your project.
What could you do to save time rebuilding models without spending warehouse credits in your next command?

A. Replace your {{ ref() }} functions with hard-coded references.
B. Leverage artifacts from a prior invocation by passing only the --state flag.
C. Clone your upstream models from the production schema to the development schema.
D. Refer to a manifest and utilize the --defer and --state flags.

Answer: D

Explanation:
The correct answer is B: Refer to a manifest and utilize the --defer and --state flags.
According to dbt's official documentation, the --defer flag enables developers to defer the resolution of model references (ref(), source()) to an existing manifest-commonly the one generated from a production run.
When this flag is used along with --state, dbt reads the prior project state and uses the already-built production models instead of rebuilding upstream dependencies. This is essential because production models are typically large and compute-intensive. By deferring to production artifacts, developers can test only the models they have modified, dramatically reducing warehouse costs and speeding up development cycles.
This approach is foundational to dbt's recommended development workflow, especially when working with CI
/CD or large DAGs. It preserves the integrity of the dependency graph while avoiding unnecessary recomputation.
Option A violates dbt best practices by removing dependency awareness. Option C is unnecessary operational overhead and does not integrate with dbt's state management. Option D is incomplete because --state alone does not prevent upstream model execution---defer is required to substitute those models with existing artifacts.

NEW QUESTION # 354
Your dbt project contains both source descriptions (within your sources.yml file) and model descriptions. You notice that the source descriptions don't appear in the generated docs alongside the relevant models. What's then most likely reason?

A. Your dbt_projectyml file is lacking the proper configuration to include source descriptions.
B. Source tables need to be explicitly tagged within your model configuration for their descriptions to appear
C. Source descriptions only appear when you navigate directly to the Sources section of the documentation_
D. A recent update to dbt has changed how source descriptions are integrated into the documentation.

Answer: A

Explanation:
The dbt_project.yml file has settings that directly control the inclusion of source descriptions in the generated documentation. Its likely that you need to adjust these settings to display them correctly.

NEW QUESTION # 355
You've been tasked with customizing the appearance of the generated documentation. Which of the following would be the most efficient starting point?

A. Write a macro that programmatically generates a new documentation structure based on your requirements_
B. Edit the json files created during the dbt docs generate process to adjust the display of information.
C. Search for third-party dbt packages designed for documentation customization.
D. Investigate overriding the default CSS and JavaScript files used by the documentation site.

Answer: C,D

Explanation:
A: Overriding the CSS and potentially JavaScript provides customization flexibility without completely rebuilding the documentation structure. D: Extending dbt's functionality with packages often offers pre-built solutions for more extensive customization of the documentation site.

NEW QUESTION # 356
You've defined a model as follows:SQL

A. A Jinja templating error: Misusing the source() function within the count() function.
B. An incorrect materialization strategy causing the wrong data to be populated in a downstream source.
C. A pure SQL issue: The count() function isn't supported for the data type of a column in the 'cust_orders' source.
D. A data type mismatch between a column in 'stg_customers' and how the query is using it for the join.

Answer: C

Explanation:
While the others might cause problems, this error message strongly indicates a database- level type incompatibility, not a dbt-specific issue.

NEW QUESTION # 357
......

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