Last week I was lucky enough to be involved in a series of workshops by Stephanie Evergreen on presenting data effectively. I've walked away with a wealth of knowledge on how to choose the most appropriate chart, which tool will create it, and how to improve the chart's design to more effectively communicate my message.
There are many ways to visualise data and depending on that data, some ways are more appropriate than others. For example, if I want to visualise parts of a whole, my first thought would be to use a Pie chart. Pie charts are great when the segments of data are few and have distinguishable values. However, when there are many segments of data, it can be easier to interpret them when they're arranged in a straight line, e.g. a Stacked bar.
Check out our page on Visualise data which can help you in choosing a way to represent your data.
Once you've decided what kind of chart you want, you need to go ahead and create it. Microsoft Excel is pretty neat at doing that for you, but you need to do a little extra work to communicate a stronger message.
The Data Visualisation Checklist, developed by Stephanie Evergreen & Ann K. Emery, can be used as a guide to help you develop a high impact data visualisation, ensuring your chart is clean and your message clear.
Stephanie ran a workshop class where she showed us how to use Excel to create charts and then the steps that can be taken to improve their effectiveness. If you missed out, here are some of her blogs which walk you through these processes:
After the workshops I got a chance to discuss some of the challenges people had with data visualisation. Here are some of the common ones:
You don't need graphic design skills or special software to make an effective data visualisation. Stay focused on the message you're trying to communicate and use your charts to emphasise that. This can be done in Excel fairly easily, and the blogs above by Stephanie show you how to do that.
You can take small steps to improve your data visualisation without veering too far from your style guide. Emphasising keywords, using shades or colour on a data set, using circles or arrows to point to a value are just a few ways in which you can direct the user's attention to the key message you're trying to communicate. All of these techniques can be used to enhance your chart without making any radical changes.
Data visualisation can have a negative impact on the viewer's ability to interpret the information, but that's due to a poorly created visualisation. Similarly, a poorly created PowerPoint presentation can distract you from the information it's aiding to deliver. It's important to always keep the message in mind when visualising the data.
There are a few ways to visualise qualitative data that I'm aware of:
Phrase Net: similar to other methods of visualising text, phrase nets connect key words in a text using lines to show linkages
Word Cloud: a visual display of the words in a qualitative dataset, organised by frequency of use
Word Tree: a visual display of the words in qualitative dataset, where frequently used words are connected by branches to the other words that appear nearby in the data
Do you know of another way to visualise qualitative data?
What challenges do you face in data visualisation?
Soon we'll be releasing a revamp of our Visualise Data section. We'll also be including some video segments of the seminar so stay tuned!