Information Visualization: Letting Data Tell the Story

Today's world involves an unprecedented amount of data. Each person is continually creating and using huge amounts of data. Human brains didn't evolve for this kind of constant analyzing, which is why data visualization is so important.

The graphic presentation of data is one of the easiest ways for human minds to wrap around vast amounts of content. Things like maps, stock charts, and graphs combine massive amounts of information into a context that is easy for the human brain to understand.

Not all data visualization is created equal. This course will show students many examples of visualization, both good and bad, and help them understand what types to use in different situations. To qualify as beautiful, a data visualization needs to be not only visually appealing but informative and efficient and interesting as well. That might sound like a lot to expect from a single visual, but this course will teach students how to create visualizations that fit the bill.

There are a few critical steps to follow when considering creating a data visualization. This class will help students understand why those steps are important.

First, understand the goals. It's important to know if information is being analyzed or presented. Will the end user need to be able to understand the data at a glance, or will they be spending more time analyzing it? Will they be using the visual once, or on an ongoing basis? Thinking about what the visual needs to achieve guides the designer in the right direction.

Then, understand the audience. Children need different visualizations than adults, experts need different visualizations than laypeople. The audience is most likely very different from the designer, and it's important to approach the problem from their perspective. A visualization is only successful if it's easily understood by the target audience.

Third, take care to only include the data that is completely necessary. Too much data can make it extremely difficult to read and comprehend a data visualization, so make sure to pare down your data. Excess information is just noise.

Designers should always follow their own intuition. These conventions are a great guideline, but if students can create a better format, they should feel free to do so. Iteration is key. A designer most likely will not create the best visualization on their first try, so they should feel free to try a bunch of different options until they land on one that they love.

Finally, focus on function first. While beautiful visualizations are great, they are only as valuable as their functionality. Don't worry too much about creating a visualization that is great art – if it's useful, it's successful.

By the time students have completed this quick course, they'll understand the state of modern information visualization, and be able to create visuals that are easily comprehensible and generate new insights on the data they show.