Data visualization is an important part of any data story. And it often garners a lot of attention because it’s one of the most fun aspects of telling a story with data. It is, however, important to note that, in our list of steps to crafting a data story, data visualization comes near the end.
Following the other steps first will help you to avoid some of the worst data visualization mistakes. You’ll avoid trying to cram too much into your viz because you’ll have identified your key story. You’ll know what results are most important to your data visualization. And you’ll have the context of those results, which is critical.
The Secret to Data Visualization
The key to telling an effective story visually is finding the right data visualization method. You need one that works for both your chosen topic and your target audience. This can be something as simple as adding photographs to your story. Not every data story needs charts and graphs. That said, if you’re going to include charts and graphs, choose carefully.
Select forms of data visualization that are appropriate for the audience you’re communicating with. Don’t fall into the trap of creating “data art” just because you can. Many things that don’t win awards are still extraordinarily valuable.
I’m a huge fan of Stephanie Evergreen over at Evergreen Data. She knows that data visualization is a great way to really engage audiences. But she also knows that poor or inappropriate viz can actually have the opposite effect. So she worked with a group of qualitative data collection and analysis researchers to develop her Qualitative Chart Chooser 3.0 — a tool designed to help storytellers select the right type of data visualization.
“In the new version, it was important for us to incorporate (1) the overall nature of the data, which drives the kind of story you can tell, (2) account for whether, in your analysis, you want to quantify the qualitative data or keep it purely qualitative, and (3) whether you want to highlight a word/phrase or display some kind of thematic analysis.”
~Stephanie Evergreen on the latest edition of Chart Chooser
(Stephanie also launched a physical version of the tool with funding from a Kickstarter campaign to make the Chart Chooser more visual and even easier to use. You can buy your deck now.)
Other Helpful Data Viz Tools
Over the years, I’ve amassed a collection of links to valuable data visualization tools and guides. If you’re ready to include viz in your data story, some of these might be helpful.
- Beth Kanter’s practical guide to Surviving Data Visualization For Non-Profits
- Kennedy Elliot’s presentation on Everything We Know About How Humans Interpret Graphics
- Creative Data Literacy details Catherine D’Ignazio’s suggestions for viz alternatives
- Our own post, Pretty Little Liars, which covers the importance of statistical literacy in data viz
- Data Wrangler from Stanford helps clean data so you can get to analysis and visualization faster
- If you use Tableau for visualization, make sure to leverage the power of Tableau Web Data Connectors
- Catherine D’Ignazio and Rahul Bhargava designed DataBasic to help nonprofits and journalists with limited data experience tell better stories
Still Have Questions About Visualization?
At Datassist, we work with journalists, nonprofits, and social sector organizations of all shapes and sizes to help them tell better data stories. If you have questions about data collection, analysis, or visualization, we can help. Get in touch with our experts today.
This is part six of our seven-part series on effective data storytelling. Check out the last two posts in the series: how to ensure your story has audience appeal and communicating uncertainty in your data story.
