As I sat cross-legged on my living room floor, surrounded by a tangle of wires, an untouched cup of coffee, and a million browser tabs, I couldn’t help but wonder: when it comes to data visualization, is the real story the one you tell—or the one you discover?
The Data School application gives you something magical: freedom. You can create a visualization (or “viz” as we aspiring data wizards call it) on virtually any topic. It’s both thrilling and overwhelming. So, how do you channel that freedom into something brilliant?
Tip #4: Pick a Topic That Sparks Joy
When I was choosing my topic, I thought, What would Carrie Bradshaw do? Okay, maybe not exactly, but I did decide to follow my heart. For me, that meant diving into my favourite TV show, Stranger Things. But for you? The sky’s the limit. Think sports, food, climate change, your favourite band—anything that excites you.
Here’s the thing: when you’re truly interested in your topic, it shows. That passion will carry you through the rough patches, like when Tableau isn’t cooperating, or your charts look more “abstract art” than “data-driven masterpiece.” Plus, choosing a topic you love gives the interviewer a glimpse of your personality—a vital trait for a consultant.
Tip #5: Tell a Story
At first, this concept baffled me. In university, storytelling wasn’t a thing in data analysis. You had a hypothesis, tested it, and voila—answers. But with data viz, you’re crafting a narrative.
The simplest way? Start with a question and answer it.
For example, “Who is the highest-grossing artist of 2024?” (Taylor Swift? Beyoncé? Don’t quote me—your guess is as good as mine.) Once you have your question, build everything around it. What charts will best communicate your findings? What data do you need? Your goal is to guide the viewer seamlessly through your story.
Tiny tip: Your story should make sense to you first. If you can’t follow your logic, neither will anyone else.
Tip #6: Find the Right Data
Now, here’s where things got a little...messy for me.
I spent two solid days scouring the internet for data on Stranger Things. Two days of importing fan ratings, analyzing popularity trends, and falling into a black hole of Reddit theories. While I don’t regret it—Stranger Things is worth every minute—I wish I’d chosen a topic with readily available data sets.
To save yourself from the same fate, start with these:
->A treasure trove of data sets for almost any topic.
->Perfect for official, reliable data.
->For niche or academic datasets.
And here’s another lesson: make sure your data includes what you actually need. Sounds obvious, right? Yet there I was, trying to chart viewer engagement over time, only to realize my data didn’t include dates. Rookie mistake. Take a moment to map out what your analysis requires before you dive into the dataset hunt.
The Golden Rule: Borrow, Don’t Build
In the data world, “stealing” is just efficient sourcing. If you can find a dataset that suits your topic, use it. Gathering and cleaning data is a labour of love—but sometimes, it’s better to skip straight to the love part.
As I pieced together my Stranger Things viz, I realized that the process wasn’t just about creating something visually appealing or technically sound. It was about connecting with my audience, telling a story that resonated, and showing a little piece of myself in the process.
So, whether you’re analysing weather patterns, predicting World Cup winners, or ranking Taylor Swift’s eras, remember: your viz isn’t just data on a screen—it’s a story worth telling.
Song of the Day:
~S xoxo