Data Story Visualization: A Decision Tree

Learn how to select the best visualization to tell your story.

Choosing the appropriate visualization for a set of data can make or break any report, presentation, or dashboard. The choice is not just about visual appeal or graphic design — it is about the story you want to tell.

Imagine presenting a chart that highlights an important trend during the past 12 months. After the meeting, the executives discuss this month’s record high measure, completely missing your point. Had you chosen the best visualization design, your point would have been more clearly discerned.

The right visualization will tell your story and make an impact on your audience. That visualization should speak for itself. Stephen Few writes that “An effective [visualization] is the product not of cute gauges, meters, and traffic lights, but rather of informed design: more science than art, more simplicity than dazzle. It is above all else, communication.” [ Information Dashboard Design, O’Reilly, 2006]

In the pandemic era when virtual meetings are creating a bigger challenge to capture and hold the attention of your audience, no one can afford to waste time trying to decode the meaning of a visualization.

How can a visualization present your story on its own?

Figure 1. A decision tree for choosing the best graphical representation.

Choosing the right visualization type is critical. Figure 1 helps you navigate through visualization choices to select the best visualization for the story you want to tell. It shows four main story narratives. Let’s walk through each of them using a case study of a bank working its way through the turbulence of a pandemic.

Change Over Time

Imagine you are a banking executive making a presentation to employees, peers, or the board of directors during economic turbulence. Use time series analysis to set the initial context for the change.

Line charts would be the key player in this presentation. They could show the unprecedented change in a single financial metric with daily, monthly, or annual granularity.

Multiple line charts are for multiple data sets that all share common units of measure, such as showing the decline in revenue, expense, and income over the same time period.

Stacked area charts show change over time for multiple data sets that together make up a whole. In this example, they can convey how each region changed over time while showing how regional totals add up to the corporate total.

Combination bar and line charts would be used when multiple data sets need to be shown together over time but which differ in units of measure. They can show staffing levels on the left Y-axis in units of people and net profit on the right Y-axis in units of dollars.

Originally published at https://tdwi.org on October 6, 2020.