Documentation, Version Control, and Collaboration

Why documentation matters

Documentation explains what a dataset, metric, query, or dashboard means and how it should be used.

• Reduces dependence on one person's memory
• Helps future analysts reproduce the work
• Speeds up onboarding for new team members
• Prevents conflicting definitions

Version control

Version control tracks every change to code and related files. Git is the most widely used system; GitHub, GitLab, and Bitbucket host Git repositories.

Never commit: passwords, API keys, access tokens, .env files, or private customer data. Add them to .gitignore and use environment variables or a secrets manager.

Useful documentation

For code: use clear names, small functions, and comments that explain why, not just what.

Collaboration

• Write descriptive commit messages: "Fix duplicate orders in revenue calc", not "update".
• Review important changes before they reach production.
• Agree on shared metric definitions in one central place.
• If two reports define "active customer" differently, explain the difference rather than assuming one is correct.

Common mistakes

• A notebook that only runs on one computer: hard-coded paths, missing packages.
• Not recording dependencies: use requirements.txt or environment.yml.
• No execution order: document the steps to run.
• Not testing from a clean environment when practical.

Try it: Create a README outline for an analytics project with sections for purpose, data, setup, methods, results, and limitations.