Data visualisation 101

As universities rely more on data to guide enrolment strategy, being able to effectively communicate data across teams is becoming a critical skill. Data visualisation is a key component of articulating data insights as the right visuals can make even the most complicated analysis easily understood. This is why we arm our clients not only with numbers but visual reports that illustrate the ‘so what?’. But, creating easy-to-digest visuals on your own can be really challenging, especially when you have a limited tool kit. If you’re new to the world of data visualisation and find yourself a bit stuck next time you’re tinkering with data in Excel or PowerPoint, try these five foundational tips shared by UniQuest Database Executive and our data visualisation guru Sophia Wallingford.

1. Clean your data
Data cleansing is a chore, but it’ll save you time in the long-run if you maintain clean data. Specifically, starting with a clean set of data will prevent formatting issues and inconsistency in your visuals. At UniQuest, we do daily data cleansing so we’re primed to create reports quickly.

2. Target your audience
Take the time to scrutinise what is ‘need to know’ data vs. superfluous detail for the person or people on the other end of your report. Trying to cram too much data into one place will raise more questions than it will answer.

Similarly, be conscious of how you’re presenting your data to your audience. Is the font large enough to be seen from the back of the room if you’re projecting slides? If printing, do your graphs and charts fit completely inside the print margins and do the colours print as expected?

3. Do some research
Considering the best way to present your data can feel quite like writer’s block. Go get some inspiration! Look to Twitter to find chatter on #datavisualization or do a google image search for the type of trend you’re trying to showcase, like change over time. There will be some examples of what to do and what not to do that will spark your creativity.

4. Change the default settings in your tools
Think about how you can customise colours and font to help your data tell its story. If you’re comparing data across different time frames for instance, perhaps a colour gradient may do the trick.

Example of a graph created and customised in Excel

mock graph
*Note: the data used in the graph above is for illustrative purposes only.

5. Be mindful of your design effects
Don’t overdo the design effects on your charts and graphs. Too many colours, styling patterns and animation and your audience won’t know where to focus. Let’s take a look at how our previous example graph would look if we amped up the colours.

blogmockgraph2

 

With so much variety, it’s difficult as the reader to decide where to look. To minimise distractions, be thoughtful about your colour and design choices and err on the side of simplicity.

As with most things, mastering data visualisation takes practice. So keep at it and take note as you go of what’s working and what’s not.

If you’re interested in learning about the student recruitment and conversion data we collect and how we report data insights to our university clients, feel free to reach Mary Evans mary@uni-quest.co.uk.

 

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