Free DBT Documentation & Version Control Questions and Answers — Questions and Answers

Question 1: Which command generates documentation for dbt models, tests, and sources?

dbt run
dbt docs generate (Correct answer)
dbt compile
dbt build

Correct answer: dbt docs generate

The `dbt docs generate` command scans your dbt project, including models, sources, tests, and their descriptions, to create a comprehensive documentation website. This command produces static HTML files that provide a detailed overview of your data lineage, model definitions, and column descriptions. It's the first step in creating human-readable documentation for your data warehouse.

Question 2: Which file is commonly used to describe fields, columns, and tests in dbt models?

dbt_project.yml
schema.yml (Correct answer)
models.sql
snapshots.yml

Correct answer: schema.yml

The `schema.yml` file (or any `.yml` file within your `models/` or `sources/` directories) is where you define metadata for your dbt resources. This includes descriptions for models, sources, and their individual columns, as well as defining tests to ensure data quality. It's crucial for documenting your data assets and enforcing data quality checks within your dbt project.

Question 3: Which dbt command is used to preview generated documentation in a local browser?

dbt docs serve (Correct answer)
dbt debug
dbt run
dbt seed

Correct answer: dbt docs serve

After generating the documentation files with `dbt docs generate`, the `dbt docs serve` command launches a local web server. This server hosts the generated documentation website, allowing you to view and interact with your project's documentation in a web browser. It provides an accessible way to explore your data models, lineage, and tests without needing to deploy the documentation externally.

Question 4: What is the purpose of writing descriptions in dbt models and columns?

To speed up query performance
To describe data models for users and developers (Correct answer)
To clean old logs
To format code

Correct answer: To describe data models for users and developers

Writing clear descriptions for dbt models and columns is essential for data governance and collaboration. These descriptions provide context and meaning to the data, making it easier for both technical and non-technical users to understand what each model represents and what data each column contains. This significantly improves data discoverability, trust, and usability across the organization.

Question 5: Which version control system is most commonly used with dbt projects?

FTP
Git (Correct answer)
Subversion
MongoDB

Correct answer: Git

Git is the most widely adopted version control system for software development, and it is also the standard for dbt projects. It allows teams to track changes to code, collaborate effectively, and manage different versions of their dbt models, tests, and configurations. Its distributed nature and robust branching/merging capabilities make it ideal for managing complex data transformation workflows.

Question 6: Why should dbt users commit changes to version control regularly?

To reduce compile time
To track project history and changes (Correct answer)
To speed up tests
To encrypt SQL files

Correct answer: To track project history and changes

Regularly committing changes to version control, specifically Git, is crucial for maintaining a detailed history of your dbt project. Each commit acts as a snapshot, allowing you to track who made what changes, when, and why. This history is invaluable for debugging, reverting to previous states, understanding the evolution of your data models, and facilitating collaborative development.

Question 7: Which Git command is used to create a new branch for feature development?

git commit -m
git checkout -b (Correct answer)
git merge main
git stash

Correct answer: git checkout -b

The `git checkout -b <branch-name>` command is used to create a new branch and immediately switch to it. This is a fundamental practice in Git for feature development, as it allows developers to work on new features or bug fixes in isolation without affecting the main codebase. Once the work is complete, the branch can be merged back into the main branch.

Question 8: Where are dbt documentation files generated by default?

docs/
target/ (Correct answer)
build/
profiles/

Correct answer: target/

By default, when you run `dbt docs generate`, the generated documentation files (HTML, CSS, JavaScript, and JSON) are stored within the `target/` directory of your dbt project. This directory is where all compiled SQL, run logs, and other build artifacts are placed. The `dbt docs serve` command then uses these files from the `target/` directory to display the documentation.

Question 9: Which practice is essential when collaborating on dbt projects using Git?

Push directly to main
Use pull requests for code review and quality (Correct answer)
Avoid committing minor changes
Only update on weekends

Correct answer: Use pull requests for code review and quality

When collaborating on dbt projects using Git, using pull requests (or merge requests) is an essential practice for maintaining code quality and ensuring proper review. Pull requests facilitate a structured review process where team members can examine proposed changes, provide feedback, and ensure that new code adheres to standards before being merged into the main branch. This prevents errors and promotes knowledge sharing.

Free DBT Documentation & Version Control Questions and Answers

Which command generates documentation for dbt models, tests, and sources?