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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Objectives
Topic 1: dbt Core Concepts	- Project structure and configuration 1. dbt_project.yml configuration 2. Packages and dependencies - Models and materializations 1. Ref and source functions 2. Views, tables, incremental models
Topic 2: Analytics Engineering Foundations	- SQL proficiency for analytics 1. Data modeling in SQL 2. Joins, aggregations, and window functions - Modern data stack concepts (ELT vs ETL) 1. Warehouse-centric transformation workflows 2. Role of dbt in analytics engineering
Topic 3: 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()
Topic 4: 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)
Topic 5: Deployment and Orchestration	- Environments and workflows 1. Development vs production environments 2. Version control with Git - Running dbt in production 1. CI/CD integration patterns 2. dbt Cloud and job scheduling

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q177-Q182):

NEW QUESTION # 177
You need to grant readonly access to the results of your dbt project to stakeholders outside your team. Considering security, which approach would be the MOST suitable?

A. Regularly run dbt seed to export CSV files, which are then shared with stakeholders.
B. Embed dbt model results within a Bl dashboard and manage access through the Bl tool.
C. Create a designated reporting schema and set up views that map to the dbt model outputs
D. Have stakeholders directly query the dbt models, providing access to the production data warehouse.

Answer: B,C

Explanation:
A provides fine-grained control within the database. C uses the Bl tool for the access management layer. B is too broad in terms of access. D is manual and less secure.

NEW QUESTION # 178
32. You are creating a fct_tasks model with this CTE:
with tasks as (
select * from {{ ref('stg_tasks') }}
)
You receive this compilation error in dbt:
Compilation Error in model fct_tasks (models/marts/fct_tasks.sql)
Model 'model.dbt_project.fct_tasks' (models/marts/fct_tasks.sql) depends on a node named 'stg_tasks' which was not found Which is correct? Choose 1 option.
Options:

A. A stg_tasks has not been defined in schema.yml.
B. There is no stg_tasks in the data warehouse.
C. stg_tasks is configured as ephemeral.
D. There is no dbt model called stg_tasks.

Answer: D

Explanation:
The dbt compilation error explicitly states that the model fct_tasks depends on a node named stg_tasks, but dbt cannot find any resource with that name in the project. dbt resolves ref('stg_tasks') at compile time by searching for a model, seed, or source named stg_tasks. When no such model exists, dbt raises the exact error shown: "depends on a node named 'stg_tasks' which was not found." This error occurs before execution and is unrelated to whether the table exists in the warehouse. For dbt, the existence of a warehouse table is irrelevant during compilation-only the presence of a declared dbt resource matters. Therefore, option C (no table in the warehouse) cannot cause this error.
Option A is incorrect because ephemeral models still count as dbt models, and dbt can resolve ref() to them without problem.
Option D is wrong because defining a model in schema.yml is optional and unrelated to dbt's ability to find the model. Tests and documentation require YAML entries, but model definitions do not.
Thus, the only correct explanation is that no model file named stg_tasks.sql exists under /models, making Option B the correct choice.

NEW QUESTION # 179
You're onboarding new developers to your dbt project. To simplify their setup, you want to provide a standard profiles.yml template. What should you consider when doing this?

A. Referencing environment variables to allow for easy customization by developers.
B. Providing example dbt commands as comments directly within the file to guide new users.
C. Prepopulating common credentials to make the initial setup hassle-free.
D. Including different target configurations to illustrate switching between development and production.

Answer: A,B,D

Explanation:
B promotes flexibility and security (avoids storing sensitive data). C demonstrates good practices. D enhances usability A is a major security risk!

NEW QUESTION # 180
Code Review

A. Additional schema tests on the model to prevent similar issues from recurring.
B. A second reviewer assigned specifically to assess the potential side effects of the fix.
C. An explanation of the error's root cause and the reasoning behind your chosen solution.
D. An updated lineage graph produced by dbt docs generate to visualize the fix's impact on dependencies.

Answer: C

Explanation:
Contextualizing the fix is crucial during code review. Docs, tests, and additional reviews are fantastic but might not always be feasible within time constraints.

NEW QUESTION # 181
You've created a macro to display upstream dependencies differently from downstream dependencies in the DAG. However, after re-generating the documentation, the visualization doesn't seem to have changed. What should you investigate?

A. Update the cache expiration settings of your web browser.
B. The built-in DAG functionality might have limitations preventing this type of customization.
C. Verify that your web browser supports the CSS and JavaScript used for custom DAG styling.
D. Ensure the macro is named correctly and located in the appropriate directory (macros folder) of your dbt project.

Answer: B,C,D

Explanation:
B: dbt needs to be able to find your macro for it to be used. C: Browser compatibility can sometimes impact the rendering of custom visualizations. D: It's possible there are constraints on how far you can modify the built-in DAG.

NEW QUESTION # 182
......

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