What is data visualisation?

Data visualisation is the representation of data through use of common graphics, such as charts, plots, infographics, and even animations. These visual displays of information communicate complex data relationships and data-driven insights in a way that is easy to understand.

Data visualisation best practices

With so many data visualisation tools readily available, there has also been a rise in ineffective information visualisation. Visual communication should be simple and deliberate to ensure that your data visualisation helps your target audience arrive at your intended insight or conclusion. The following best practices can help ensure your data visualisation is useful and clear:

Set the context: It’s important to provide general background information to ground the audience around why this particular data point is important. For example, if e-mail open rates were underperforming, we may want to illustrate how a company’s open rate compares to the overall industry, demonstrating that the company has a problem within this marketing channel. To drive an action, the audience needs to understand how current performance compares to something tangible, like a goal, benchmark, or other key performance indicators (KPIs).

Know your audience(s): Think about who your visualisation is designed for and then make sure your data visualisation fits their needs. What is that person trying to accomplish? What kind of questions do they care about? Does your visualisation address their concerns? You’ll want the data that you provide to motivate people to act within their scope of their role. If you’re unsure if the visualisation is clear, present it to one or two people within your target audience to get feedback, allowing you to make additional edits prior to a large presentation.

Choose an effective visual: Specific visuals are designed for specific types of datasets. For instance, scatter plots display the relationship between two variables well, while line graphs display time series data well. Ensure that the visual actually assists the audience in understanding your main takeaway. Misalignment of charts and data can result in the opposite, confusing your audience further versus providing clarity.

Keep it simple: Data visualisation tools can make it easy to add all sorts of information to your visual. However, just because you can, it doesn’t mean that you should! In data visualisation, you want to be very deliberate about the additional information that you add to focus user attention. For example, do you need data labels on every bar in your bar chart? Perhaps you only need one or two to help illustrate your point. Do you need a variety of colours to communicate your idea? Are you using colours that are accessible to a wide range of audiences (e.g. accounting for colour blind audiences)? Design your data visualisation for maximum impact by eliminating information that may distract your target audience.