Viz What You Love
By: Zach Bowders
Tags: Movies, Information Design, Pop Culture, Design, Data Visualization

Viz What You Love

A geek‘s guide to leveling up your data visualizations

Data visualization is a great way to celebrate our favorite pieces of art as well as reveal connections and ideas that were previously invisible. More importantly, it’s a fun way to connect things we love — visualizing data and kicking up our feet for a movie night. All week, Nightingale is exploring the intersections between data visualization and all kinds of entertainment.

After a long day of meetings, projections, and rigorous data analysis there’s nothing I look forward to more in the evening than sitting down and fiddling with a Business Intelligence tool.

Really. I’m not joking.

You might think I’m getting paid to say this (I’m not), but most evenings, while my girls are falling asleep next door, I’m sitting in my office in the same chair I worked in all day, building data viz in Tableau.

For fun.

Because I’m making art.

I’m not bold enough to call myself an artist but I’ve always been into drawing. Whether it be in class, a meeting, or watching TV you’ll find a pencil in my hand and images appearing on a piece of paper. While the tools have changed over time, from a Bristol pad and Dixon Ticonderoga to iPad Pro with Magic Pencil, the art and doodling has been constant.

Let’s get back to data viz.

I’ve been actively creating data visualization on Tableau Public for about three years now and have a portfolio of over 140 visualizations. A lot of my early work was driven by public data exercises that really helped me establish a connection to the #DataFam community as well as skill up.

When you’re really trying to get traction, these exercises are PERFECT. With the same tool and dataset you see hundreds of different vizzes every week. If someone else created something better/cooler/smarter than your work, the only thing keeping you from getting there is your own skillset and creativity.

But I started to find that community exercises didn’t always produce my best work. It’s not their fault, it’s entirely mine. If I felt uninterested in a topic or dataset I tried to make myself more interested. Bold color choices, weird chart types, lots and lots of unnecessary graphics. It was counterproductive.

I wanted to learn AND make art.

Thinking back to what originally got me excited about DataViz early in my career, I remembered a visualization by Rody Zakovich analyzing the legendary rock band Queen. Rody transformed what I thought a data viz could be.

Queen’s albums, weighted by words, tapering into a single point from Freddie Mercury’s spiked fist.

(Here’s the chart, sans Mercury)

What! You can do that?

I was taken with the cleverness and elegance of the design, but what really caught my attention was the passion. Rody had taken a topic he was personally fascinated by and elevated it with data. And it wasn’t really that hard. Yes, he used trigonometric functions to bend the lines at the bottom, but we’re really looking at 4 relatively simple charts here. BANS across the top, bar charts, a colored text table, and then some bent lines.

The combination, and the passion behind it, were what captured my imagination.

So, the question is, why wasn’t I working on projects that covered MY interests?

Cards on the table, I’ve been a geek since long before it was cool. I blasted through Jurassic Park (my first novel) in a brazen 24 hour binge as an 11-year-old. I read Star Wars expanded universe novels in middle school (in class, no less), and sketched pictures of Batman and the X-Men for friends.

While my tastes have progressed, I’m still a comic reading, sci-fi loving, pop-culture junkie. And we now live in an age where that’s become mainstream.

What could I learn, what could I REALLY do, if I chose to work on things that captured my attention?

Data viz is about translating difficult to grasp concepts into easy-to-understand visuals. While bars, BANS, lines, and maps may be the bread-and-butter of the discipline, there are other ways to express these ideas.

This led me to ideas like mapping the dreamworlds of Inception. Christopher Nolan’s complex dream-heist masterpiece can be complicated to wrap your mind around (believe me, I had to figure out how to make an image of it), but it was an EXCELLENT opportunity to practice Cartesian mapping of lines.