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Data visualizations – you can’t escape them. They can give you quick facts about famous athletes and celebrities. They can break down complex topics such as supply chain management functions and the content management life cycle. Data visualizations go by names such as charts, graphs, and infographics, but not all data visualizations are created equal, nor are they all created well.
Bad data visualization can undermine the information sharing you want to achieve while effectively killing your content. Start with the resources and tips below so you can present your visual content in the best possible light before putting your next data visualization project into place.
Image via Stats Chat
Knowing how to present data in a chart starts with figuring out what you’re attempting to visualize in the first place. If you can’t articulate what you want to explain, you could be left with a data visualization like the example above.
While the overall circular shape of the graphic is perplexing, what’s worse is the amount of data being crammed into the chart. Simple, easy to understand data visualizations always win out over flashy graphics and designs that do little more than complicate a concept and frustrate viewers.
Image via e-Training Institute
Nothing kills a data visualization faster than a data presentation that simply doesn’t make sense. The above data visualization illustrating how baby boomers describe themselves is particularly problematic in the presentation of its data. At first glance, you’re led to believe that the percentages represent the parts of a whole person, but the total you get when you add the individual percentages together is 243 percent.
This data visualization would’ve benefited from a data treatment that simply focused on the individual percentages themselves. Instead, this visualization gives the impression that the sum of the parts makes up the whole. When working with stats, be sure that the method in which you choose to present them is logical.
Image via Infographics Archive
As noted earlier, data visualizations are pervasive across the web. You might think that every piece of content you create needs to be represented by a data visualization, but creating one simply for the sake of creating it is a bad data visualization strategy.
Forbes contributor Jason Oberholtzer makes this point clear in his commentary on the infamous Attack of the Debt Monkey infographic created for Money Rates in 2012. The premise of the infographic was intriguing enough, visualizing increases in United States debt, but Oberholtzer observes a few puzzling, and perhaps disturbing, issues with this infographic design.
We’ll get to the disturbing part in a moment, but first let’s look at the item in the infographic related to personal and government debt. What does personal debt have to do with government debt? Why represent these figures with percentages?
Now for the disturbing part. As Oberholtzer observes, debt, as the monkey on our backs, was taken to the extreme with the somewhat disturbing visualization of government debt, symbolized by a gorilla, compounding personal debt (and taking off the data figure’s head in the process). The infographic concludes with a visual of the data figure feeding bananas to the debt monkey, despite the text above the illustration that reads “But is it time you stopped feeding your own debt monkey?”
Now that we’ve covered the debt monkey and other bad data visualization examples, let’s talk about what you can do to improve or avoid poor data visualizations in the first place.
A good data visualization should communicate a story at a glance. The actual text you use should support the visuals, not override or clutter their presentation. Be purposeful with your data and research. Don’t create bar graphs and cute, but unnecessary pictograms simply for the sake of creating them. Every piece of data you choose to represent should serve a purpose and connect to the overall story you’re telling. Every element of text you choose to include should support the visuals and not add unnecessary fluff.
Image via Gates Notes
“There’s more than one way to do it” is an axiom that definitely applies to data visualizations. Before creating your own, take some time to research what other people have created. Inspiration abounds when you know where to look for it.
The Gates Notes, the personal blog of Bill Gates, took an innovative approach to talking about malaria without ever mentioning the disease directly. The data visualization above describes the world’s deadliest animals and the number of people who’re killed by those animals each year. It ends with one sobering statistic – the mosquito is the deadliest animal represented in the visualization.
This simple, yet provocative data visualization accompanied a blog on Gates Notes devoted to Mosquito Week that further detailed the health crisis related to diseases transmitted by mosquitoes across the globe.
Execution is everything with data visualizations. You may have superb facts and a compelling story to present, but a cluttered data visualization concept with a color palette that clashes against your typography choices can make a good idea turn into a bad data visualization nightmare in no time.
Establish your color palette and typography choices first before you start the designing phase. If you don’t have the luxury of tapping the talents of in-house graphic designers, you can find a number of useful data visualization programs with design templates that can help you get started.
Don’t let bad data visualization kill the content you’re trying to promote. Use the resources and suggestions presented above to help you create effective and pleasing data visualization designs. Your work should engage, enlighten, and inspire members of your target audience to share your infographic or graphic visualization. The target audience should connect with the message that you and your brand are trying to communicate.