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Tips and Tricks

5 Tips for Building Better Data Visualizations

The process of data analysis is about more than just finding insights that are valuable to a business. If those insights don’t turn into actions, they aren’t helping the company. In order for a data insight to be of maximum value, an analyst has to explain it to other decisions makers in a way that will convince them to translate it into action.

The best tool in the analyst’s toolbox is a convincing chart, a visual that will illustrate the insight clearly. Periscope Data discovery for business allows a new wave of citizen data scientists to share their insights in charts, but building a sound chart is a skill that takes a lot of work to perfect. We already shared a flow chart to determine the right chart to use, but when it comes to the construction of that chart, there are a few simple tips that can go a long way toward optimizing the story that the data is telling.

Below are five tips from the Periscope Data team to help you build effective charts from your data. If you are looking for more information on data analysis and visual storytelling, download our How to Chart Your Data Discoveries guide.

Tips for telling the right story with charts

  • Include descriptive titles on charts. The data in a chart will tell the story, but you have to set the stage with a title before that can happen. A chart that shows an up-and-to-the-right hockey stick is valueless without knowing whether you’re looking at profit for a company or complaints to the support team. A good rule for chart titles is to be descriptive. Labeling the visualization with the name of the variable or variables you’re showing is usually a good idea. When you think about the chart as part of a bigger dashboard with other charts, it is especially clear that the information is labeled correctly.
  • Avoid clutter. The point of a chart is to illustrate a specific phenomenon or trend clearly. Having extraneous information in that visual is going to distract from the intended narrative or even block people from seeing it altogether. Before finishing a chart, examine it for information that isn’t needed, even taking into consideration the axes and chart infrastructure.
  • Ask yourself if the chart illustrates the insight without explanation. Between the title of the chart and the trend that is illustrated by the data, the insight gained from that information should be clear. Keep in mind that once charts are made, they might be shared or consumed by other people who won’t have the benefit of reviewing the information with the chart’s creator. Charts will also be included in broader dashboards where the information will need to speak for itself to tell a bigger story, so the discovery should be clear without much investigation.
  • Advanced tool: mixing series types. Bar, line and scatter charts can be mixed and matched to allow you to put multiple pieces of information into a single graph. Use series types to show the difference between unique categories of data, such as a line and a bar for a Y1 and Y2 axes, or a bar and a scatter to show the realized revenue and projected revenue.
  • Use color as a tool, not an accent. Color can be crucial to the way a reader understands a chart, so don’t be afraid to use it as part of your story. Consider the following chart, which displays a change in daily active users. It shows a pretty clear picture of volatility.

Now consider the same chart, colored differently, with green to show increases and red to show decreases. Adding this color shows a different story — not just that the daily active user count is volatile, but that the gains and losses come in multi-day chunks. Now the story shifts from showing instability to questioning the cause of this pattern.

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Britton Stamper
A self-described data visualization evangelist, Britton spends his time working with and teaching anyone who will listen about the great benefits of aligning a visual’s design with a business need. He’s willing to go to any length to get people to understand the need for including data in decision making.