Business dashboard design: The fundamentals of data visualization
Choosing the right data visualizations is at the heart of all successful business dashboards. What is a successful dashboard? you may be wondering. It's one that serves its user's needs and integrates seamlessly into their day-to-day work.
There are tons of visualizations to choose from, but not all are the right match for your data. A well-designed dashboard is compact, clear, feels familiar, and allows for rapid scanability.
This is in addition to being customized based on a variety of ancillary preferences, including color and color theming (like the dashboard below):
Proper use of data visualizations helps to bring these important qualities to your dashboard.
Here are 8 common data visualizations for business dashboards:
- Bar charts
- Line charts
- Pie charts
The following blog post will briefly highlight each element and offer some guidance on when to (and when not to) bring each of them onto your business dashboard.
1. Bar charts
Bar charts organize data into rectangular bars which makes it easy to compare related data. Bar charts are a popular visualization because most people are familiar with how to quickly scan them.
Bar chart visualization best practices:
Map visualizations organize data geographically. If your dashboard is looking at monthly sales, it could be useful to see the geographic locations of your customers. But if the dashboard is looking at daily sales, this visualization may provide less value to the user's day-to-day.
Map visualization best practices:
3. Line charts
Line charts visualize data in a compact and precise format which makes it easy for users to rapidly scan information to understand trends. The proper use of color in this visualization is also necessary because different colored lines can make it even easier for users to analyze information.
Line chart visualization best practices:
Before using a scatterplot to visualize your data, ask yourself how the dashboard will be accessed by the user and if they need precise data points from the metric.
Scatterplots are typically not the clearest way to scan information, so if the visualized data is being shown on a TV dashboard, it will be difficult to quickly understand the displayed quantitative measures.
This data visualization can be most useful when quantitative measures are frequently changing and a user's day-to-day monitoring would benefit from seeing those changes.
Scatterplot visualization best practices:
Sparklines are arguably the best data visualization for showing trends on a business dashboard with many metrics because of how compact they are. It’s important to make sure your audience understands how to read sparklines to optimize their use. To assist in this readability, consider adding indicators on the side that give a deeper glimpse into the data.
Sparkline visualization best practices:
6. Pie charts
Everyone has a love-hate relationship with pie charts. At a high-level, they're easy to read and understand because the parts-of-a-whole relationship is made obvious.
But top data visualization experts agree that they should not be used because the percentage of each section isn’t obvious without adding numerical values. So what’s the point?
Pie chart visualization best practices:
Gauges are different from other data visualizations because they typically only compare two values: a current value and its scale to determine good or bad (often indicated through a target value).
Gauge visualization best practices:
Tables organize data into columns and rows. They're great visualizations because you can display both data points and graphics such as bullet charts, icons and sparklines. For dashboards with many metrics, tables can sometimes be overwhelming depending on how much data you choose to display.
It's important to find a happy medium between large amounts of data (confusing) and too little data (waste of dashboard space).
Table visualization best practices:
Final thoughts on data visualizations for dashboard design
This list is not all the options you have for data visualizations. Others include area chart, donut chart, horizontal and vertical gauges, spark bar, win/loss chart, bubble chart, pictograph, bullet chart, and funnel chart. The list really goes on!
It’s also important to mention that data visualizations aren’t limited to color, icons, and overall design. In other words, your data isn't rendered visually useless just because it doesn't quite work in one particular form of data visualization.