When you're dealing with a chart that has too much information on it, the most straightforward advice to follow is: break it down into multiple charts, each with less information on them. A powerful example of this is a so-called small multiple approach.

Spreadsheet tools such as Microsoft Excel or Numbers might not be the first thing on your mind when considering data visualization tools, but they can be pretty solid choices to build data visuals. Don’t let anyone convince you that using Excel to create data visuals is unprofessional.

Fonts evoke emotions: there are very sophisticated fonts, playful fonts, attention-grabbing fonts, and elegant handwritten fonts. Using the wrong type of font can have a lot of impact. In data visualization the implications of typography are mainly focused on readability. Labels and annotations can easily become so small they get hard to read. Above all else, we should choose a font which is readable at small sizes.

Colour is one of the most crucial tools we have to turn a normal chart into a powerful chart with a clear message, a chart which tells a story rather than simply presenting the information.

A crucial step in building a powerful chart is choosing the right type of chart. A lot of charts don’t work because they simply use the wrong type of chart. To avoid this trap, we must ask ourselves a basic question: what’s the ultimate goal of our data visual? What do we want to show with our data?

Removing noise from a data visual is not only about taking things away such as gridlines, axes or legends. That’s just one part of it, which we could call removing physical noise. Improving the signal-to-noise ratio is often also about adding little things that help our audience better understand the visual. We are helping them by removing mental noise, or mental barriers.