Evaluating Data Visualizations
Data visualizations can be very colorful and impressive. But remember that the key to creating effective data visualizations doesn't hinge on whether it's exciting, but rather on whether it uncovers the real business issues that need to be addressed. A worksheet helps you create your own data visualizations or evaluate the creations of others.
Here are just a few categories to consider when you're evaluating a data viz:
Big-picture considerations: When you begin to analyze a data visualization, you need to start with the foundational items that shape the overall design. These include such things as how much data to include and how to make it easy to understand.
Color: People are affected by color, so choosing complementary ones are important. You also need to make sure to use them consistently so that you don't confuse the viewer.
Design issues: Design issues are key on the web. People have come to expect a certain level of sophistication, so strive to make your data visualization look well thought-out.
Text formatting: Because you're limiting the text you use, you need to make each word useful and understandable.
Menus: Web users expect working menus that add value. Test to make sure they all work as expected.
Interactivity: The key to good data visualizations is their ability to help users analyze different data sets. Think carefully about what you choose to use as what-if scenarios.
Design for mobile: When you create data viz, assume that some of your users will be mobile and make sure the design is suitable for different devices.
Use this Worksheet for Evaluating Data Visualizations (Microsoft Word required) to take careful notes about what does and doesn't work. It'll help you improve your chances of creating solid data visualizations.