Why is data visualization so powerful?
The amount of data coming our way is growing exponentially. In 2021 alone, it is estimated that humankind generated 74 zettabytes of data – that’s about 10,000 GB per person. How on earth are we going to keep this manageable?
Visualization: our most powerful tool
Visualization is one of the key solutions to cope with the endless stream of data, content and information – together with other strategies such as filtering and organization. Visualization might very well be the most powerful tool we have to turn complex information into manageable insights. But why is that?
There are three important reasons why data visualization is a very strong way to present information:
- its information density is extremely high,
- it attracts the attention of your audience, and
- visual information is easier to process and memorize.
Reason 1: information density
Researchers at MIT have shown that we can detect the meaning of a picture in as little as 13 milliseconds – that’s extremely fast.
We could spend hours looking at this dataset for example, created by visual journalism professor Alberto Cairo, without learning anything. But as soon as we turn the data into a scatter plot, it’s obvious that we’re looking at a dinosaur. In the blink of an eye!
Reason 2: attractiveness
Visual information is also attractive. Not in the sense that it is beautiful to look at (although that’s often also our goal), but literally: it attracts the attention of your audience. In a book or newspaper, people will often look for the pictures first, before they start reading all of the text.
Reason 3: easier to process
Finally, charts and infographics are easier to process than written text. The dual-coding theory, developed by Allan Paivio, states that our brains process information both in a visual, as well as a verbal way. If we only get verbal stimuli, only a part of our brain is working. That’s why during a long phone call we automatically start doodling – the visual brain is bored and looking for things to do. By providing our audience with a combination of text and images, the entire brain is stimulated, leading to better focus, better understanding, and better memorization.
Harnessing the power of data visualization
So in summary, data visualization is powerful because it combines a high information density, attractiveness, and easier processing and memorization.
If you want to know more about visualizing data in the right way, you can check out the other videos in this series. Or I invite you to read my book, Powerful Charts, that will give you actionable insights and practical guidelines to create data visuals that truly engage and inspire your audience.
Full video series
- 01. Why is data visualization so powerful?
- 02. Why is data visualization so challenging?
- 03. Navigating the landscape of powerful charts
- 04. A powerful chart tells a story
- 05. A powerful chart has a high signal-to-noise ratio
- 06. Making a data visual noise-free
- 07. 7 different goals for your chart
- 08. Three roles of colour in a data visual
- 09. Choosing the right font for your data visual
- 10. Can you use Excel to create a powerful chart? (coming on January 09, 2023)
Read more:
Choosing the right font for your data visual
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.
2 January 2023
Three roles of colour in a data visual
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.
26 December 2022
7 different goals for your chart
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?
19 December 2022
Making a data visual noise-free
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.
12 December 2022
Three tips to create powerful charts in Excel
Creating charts in Excel can be a very powerful tool for making sense of complex data sets, and for visualizing them. But the default options are not always the most pretty or effective ones. Here are our top three tips to create better Excel charts.
8 December 2022
A powerful chart has a high signal-to-noise ratio
‘Less is more’. It’s a crucial principle in most of our communication, and in data visualization in particular. Because of my background as a physicist, I prefer to talk about the ‘signal-to-noise ratio’. The message - our signal - should be amplified as much as possible, giving it all of the attention. Everything that can distract from our message - the noise - should be removed.
5 December 2022
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