Laura Learns Data

I’ve been meaning to do this for a long time. As someone who works in data, I’ve always known that having a GitHub profile is kind of expected — but for a while it felt like something that was more for software engineers than for people like me who spend most of their time in Tableau and SQL. Then I started seeing more and more data analysts sharing their work on GitHub, and I realized I was leaving a pretty easy opportunity on the table.

So a few weeks ago I finally sat down and set one up. Here’s what I did, what I learned, and what I’d tell myself if I were starting over.

Step 1: Sign Up and Claim a Good Username

This sounds obvious, but spend a minute thinking about your username before you commit. It’ll be in your profile URL and on anything you share publicly. I went with something close to my actual name — simple and professional. You can change it later but it’s a pain, so get it right from the start.

Step 2: Create Your Profile README

This was the thing I didn’t know existed and now I think it’s the most valuable thing on my whole profile. Here’s how it works: if you create a repository with the exact same name as your GitHub username and add a README to it, GitHub automatically shows that README front and center on your profile page. It’s essentially a free homepage.

I kept mine straightforward:

• A short intro about who I am and what I do
• The tools I work with (Tableau, SQL, Python, dbt)
• What I’m currently learning or exploring
• Links to this blog and my LinkedIn

You write it in Markdown, which is pretty easy to pick up if you haven’t used it before. GitHub has a guide to profile READMEs that’s worth a quick read.

Step 3: Create Your First Repository

A repository (or “repo”) is basically just a folder for a project, with built-in version tracking. For my first one, I didn’t try to do anything fancy — I just uploaded a Python script I’d already written for some Tableau Server admin work, added a README explaining what it does and how to use it, and pushed it live.

That’s really all a repo needs at minimum: the actual files and a README that explains what you’re looking at. For data projects specifically, I’d add:

• What problem the project solves
• What tools/languages you used
• A sample of the output or a screenshot if it’s visual

Step 4: Pin Your Best Work

GitHub lets you pin up to 6 repositories to the top of your profile. These are the first thing people see, so be intentional about it. I’ve only got a couple of repos so far, so mine are both pinned — but the advice I’ve seen that resonates is: 3–5 polished projects beats 20 half-finished ones every time.

Step 5: Don’t Stress About the Green Squares

You know those contribution graphs — the grid of green squares that shows how active you are? I spent about five minutes worrying about mine being mostly empty before I decided it just doesn’t matter right now. Building the habit of committing work there consistently takes time. The point right now is to have something to point people to, not to look like I’m shipping code every day.

What I’m Planning to Add Next

Honestly, my GitHub is pretty sparse right now and that’s fine. I’m thinking about adding:

• A repo for some SQL query templates I find myself reusing
• Any Python scripts I write for Tableau automation (building on my last post!)
• Maybe a portfolio-style repo that links out to my Tableau Public work

The nice thing is that it doesn’t have to be perfect to be useful. Having something is already better than nothing.

If you’ve been putting off making a GitHub like I was, just do it. It takes about 20 minutes to get something real up there, and future-you will be glad you did. Feel free to share your profile in the comments — I’d love to see what others are building.