Join Bill Shander for an in-depth discussion in this video Story, part of Data Visualization for Data Analysts.
- Okay, time to go through 10 easy lessons for data visualization for data analysts. The first lesson is about story. Visualizations are more than just data, they're more than just charts or maps. At best, they really are stories. If you think about, from the dawn of time, humans have always communicated via story. Cavemen didn't come back from the hunt and have a spreadsheet to share how many arrows they used and how many miles they ran to chase down the buffalo. They told a story. Their stories contained all the data, but that wasn't the point.
The point was really telling a story, and that's how the story got handed down generation to generation. There's really proven brain science for why that is, why it worked out and why we're wired for story. So the theory is that our brains are wired for story because our brain's primary job is to contribute to our survival. It does this mostly by helping us understand what might happen in the future based on past events, either those that we've experienced or that we've heard about through story. Effective stories reach us because they give us what the brain craves, a sense of urgency about what happens next. So communicating data, like communicating anything, is about reaching your audience in a way that they can related to.
Stories really are the best way to do this. But that doesn't mean that every data visualization is a quote, unquote storytelling experience. However, it does mean that the more you can use the structure of a story, no matter how simple, the better off you'll be. Every story has a beginning, middle and end. You remember this structure. If you think of everything that you create as being in this context, even a single slide, the better off you'll be. Some stories have a more nuanced look, like this. There's a beginning, the challenge, the middle, climax, et cetera, but really, beginning, middle, end is good enough to think about.
Let's say you're creating some infographic. First thing, you define the headline. Maybe you have more than one headline. I always like to suggest that you think of headlines in a specific way. Think about The New York Post versus The New York Times headline. Simple and fun and crazy, more serious and fact based. What will people tweet about? What you wanna do when you're thinking of your headline also is you wanna have blanks spaces. In other words, you don't wanna fill in the entire headline, especially when you're doing the data analysis. You can't have already decided what the story is, but you need to come up with great headlines before you even work on your project to really know what you're trying to communicate.
What's the next part of the story? There's an introduction. There's text maybe at the top of this infographic to introduce the idea. It establishes the premise and the context before your reader dives into the data. The beginning is done, now it's onto the challenge part of the story. So maybe the challenge is just in a big subheader below the introductory text. Maybe this is really some bold type to draw the eye. This is a simple way to do it. This is sort of your wire frame form of an infographic. That's a challenge. My eye is gonna go there and it's gonna sort of set something up, set up the rest of the infographic for me.
The middle of the story is really the meat and the potatoes, so this is like the chart with all the details and the interactivity and the imagery where the user spends most of their time. How does the user introduce the climax? Maybe it looks like this. If this is the meat of the story, this is a flow chart infographic, let's say, this might be that climax moment. I'm really drawing the eye to you. While the user may not ingest your infographic in this way, they may not read it in a linear way, the structure of it follows that pattern, which is how people really think about these things.
If you're creating an interactive infographic, of course, you can literally walk them through a linear story by creating interactivity that makes the story come out. Or you can have all sorts of filtering and sorting buttons to really bring the story out in the order that you wanna tell it. You can encourage the user to click certain filters first. And, of course, you can draw the eye to things when you want to draw the eye to that climax or some interesting part of the story, either based on a click or a filter or some sort of user action. If we go back to our static infographic example, it's also really easy to offer a conclusion, the end of our story on our page.
Maybe you have a small print footer with your data sources and some conclusion information. Structurally, it's very easy to see what the conclusion is for this infographic. If you think of every project you do, even nonlinear ones, even static graphics, within a linear storytelling framework, it'll help you think through the logic. It'll help you think through the functionality, if it's interactive. Even though you might not always be telling a traditional, linear story, you just wanna remember when you're wearing the hat of a data visualizer, you're in storytelling mode, you're not in data analyst mode.
So tell a story and connect with your audience.
- Why visual communications matter, and how they work
- Communicating via story
- Communicating with color
- Using legends and sources
- Sketching and wireframing
- Rethinking slides, charts, and diagrams
- Rethinking your templates and brand guidelines