Analytics and data – on their own – are relatively useless. The only way to unlock the full potential of these important assets is by using strong visualizations that connect your audience to the meaning inside. It’s time to stop doing your data a disservice and start investing in powerful visuals that do your hard work justice.
Six Ways to Improve Your Data Visualizations
The purpose of any data visualization is clear. It’s designed to clearly convey the meaning behind specific numbers and data points in a manner that’s easy for the viewer to digest and understand. It’s supposed to be an attractive graphic representation of numbers that are otherwise lifeless and meaningless.
Improving your data visualizations may seem like a lofty task, but it simply requires a concerted effort from your team. Here are a handful of practical ways you can begin enhancing your visualizations as soon as today:
When it comes to exposing data via visualizations, there are two primary things to think about: the audience and the story. “Knowing who your audience is will help you to determine what data you need,” explains Jac Reid of datapine. “Knowing what story you want to tell (analyzing the data) tells you what charts to use.”
Your audience is the single most important consideration. If you don’t connect with the audience, then it’s impossible to have positive results. Then you have to think about what story you want to tell – and whether it will resonate with the audience. Once you figure out these two aspects, everything else falls into place.
2. Choose the Right Charts
Let’s dig a little deeper into the aspect of choosing the right chart. “In general, there are two basic types of data visualization: exploration, which helps find a story the data is telling you, and explanation, which tells a story to an audience,” Datalabs points out. “Both types of data visualization must take into account the audience’s expectations.”
Once you know what story you want to tell your audience, you’ll understand whether or not the purpose is to explore or explain. At this point, you’ll have to do your research and determine which type of visualization is best for your data. There are cartograms, scatter plots, pie charts, histograms, dendograms, matrices, tree diagrams, bar charts, line graphs and much more. Choose wisely!
3. Provide Context
Data visualizations can’t be successful unless they provide the audience with context. This is something that most businesses forget – and is the primary reason why the majority of visualizations fail to be more successful.
The audience has to understand where the data is coming from, what it represents, and what the results are suggesting. If they don’t see any relevancy, it’s impossible for them to fully understand what’s happening or why the data is valuable.
4. Keep Things Simple
There’s always a temptation to pack as much information as possible into a single visualization, but this is a mistake that must be avoided. The more information you throw at the audience, the less information they absorb or remember.
Just as minimalism is sweeping through the web design world, it’s also becoming a bigger and bigger priority in data-related fields. As businesses are able to access more and more data, the temptation is to include that data in visuals. Unfortunately, this doesn’t always end up well.
“Some information visualizers, especially those working at newspapers and magazines like [National Geographic], worry that complex visualizations make beautiful data art, but that they risk confusing readers instead of enlightening them,” data visualizer and journalist Geoff McGhee says. If you want to produce visualizations that are relevant and appealing, simple is the word.
5. Label the Data
Everyone wants to take a “less is more” approach to data visualization, but you have to be very careful. Data visualizations need to be adequately labeled in order to provide the audience with enough contextual clues to identify the story you’re attempting to tell.
As a rule of thumb, try to avoid using a legend or key whenever possible. This requires the reader to look at the visualization, reference the key and then return to the visualization. This confuses some people and dissuades others who don’t want to spend time deciphering the message. When possible, always use clear labels inside the visualization itself.
6. Use a Visualization Tool
The great thing about working with data in 2016 is that you have access to a slew of powerful tools. Instead of trying to manually make visual sense of your data, use one (or more) of these resources to simplify the process. Not only do these tools make your data clearer, but they also save you time and money – allowing you to allocate resources to other areas of the business that directly impact your bottom line.
Maximize Your Data
Collecting, filtering, and organizing data isn’t easy. It takes time, effort and strategic forethought. Sadly, many businesses squander the opportunity to make the most out of their investment by failing to utilize the right visualizations. It’s time that you start maximizing your data and enjoying the benefits by leveraging stronger visualizations.