Most people think documentation is just an afterthought something you do at the end of a project to keep things tidy.
But here’s the truth: Documentation isn’t just about writing things down; it’s a strategic tool that makes you a better data professional.
I don’t just document my work after the fact. I start before I even write a single line of code. Why? Because every decision you make, from choosing a project topic to selecting the right tools, impacts your final outcome.
📍 What Should You Be Documenting?
If you’re only documenting code, you’re missing the bigger picture.
Here’s what you need to track in every project:
✔ Project Title & Overview:
What’s the project about? What’s the goal? A clear overview helps anyone (including future you) quickly understand the project.
✔ Problem Statement
What challenge are you solving? Why does it matter? This keeps your work focused and meaningful.
✔ Tool Selection: Which tools will I use and why? Maybe Python is better for automation, but SQL is more efficient for data extraction. Documenting this helps you reflect on your choices later.
✔ Data Sources and preparation: Where is my data coming from? Is it reliable? Did I preprocess it? If you revisit the project in six months, you’ll want these answers.
✔ Decisions and Changes: Every major decision—why you used a certain algorithm, why you cleaned data a specific way—should be logged. This prevents “past you” from confusing “future you.”
✔ Key Insights & Learnings: What worked? What didn’t? What trends did I uncover? This is where the real value of your work shines. What would I do differently next time? These notes become your personal knowledge base. And it turns every project into a learning experience.
✔ Recommendations & Next Steps
What should be done based on your findings? Are there improvements or further research needed? This makes your work actionable.
📍 Where Do I Document?
•➤ For Quick Brainstorming → Paper: Nothing beats handwritten notes for capturing raw ideas and sketching out workflows.
•➤ For Ongoing Documentation → Digital Tools (GitHub, Notion, Google Docs, Jupyter Notebooks):
• Easily updated and searchable
• Allows me to add screenshots, links, and code snippets
• Keeps my workflow structured and accessible
📍 Why This Matters
Great data professionals don’t just analyze data; they think critically, track their thought process, and refine their approach over time.
If you’re not documenting your work, you’re making your job harder than it needs to be. Start early, be intentional, and turn documentation into a competitive advantage.
Your future self will thank you.
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