Data visualization is one of the basic methods of presenting information in a graphical way. It involves presenting data in the form of charts, tables, or maps to facilitate understanding. However, data storytelling visualization is more than just a regular visualization. It is a method that not only presents data in an accessible and attractive way but also enables storytelling using data. Yes, storytelling. It is a type of storytelling that allows audiences to understand complex relationships and patterns hidden in data. In this article, we will discuss what data storytelling is exactly and what benefits this data visualization method brings.
What is data visualization?
Data visualization is the process of presenting information using graphics, charts, maps, photos, and other images. This makes data easier to understand and assimilate for audiences. Well-designed data visualizations are effective because they present complex information in a simple way. Data visualization is not just a chart or diagram, but actually a representation of data that helps understand its significance.
What is data storytelling?
Data storytelling is the process of creating a narrative using data. This means that using data, we can tell an interesting and persuasive story. Because data visualization makes it easier to assimilate information, it is ideal for data storytelling.
What tools to use for data storytelling?
Various tools can be used to create data visualizations. There are many available on the market, including Excel, Tableau, Power BI, Google Charts, D3.js, Infogram, QlikView, Highcharts, Plotly, FusionCharts, Grafana, Matplotlib, and many others. The most important thing is to choose a tool that best suits the needs and skills of the audience. Compatibility with other work environments and colleagues is equally important. For these reasons, I believe that the most powerful set of data visualization tools is the Office package - with Excel, which can calculate, compile, and visualize complex data, and then transfer it to a presentation tool that works very well with it, such as PowerPoint.
What data visualization in the form of data storytelling is NOT:
- A set of unrelated complicated charts and tables that do not create a coherent story.
- Presentation of a huge amount of data from which it is difficult to extract the essence of information.
- Data visualization that does not appeal to emotions and does not encourage reflection from the audience.
What a good data visualization in the form of data storytelling IS:
- A simple, understandable, and accessible visualization that does not overwhelm the audience with too much data.
- A story focused on showing step-by-step intertwining threads of one case study, conclusion, story, or issue.
- Data visualization that increases audience interest, puts them in a state of focus, stimulates imagination and emotions.
- A story that leads the audience through the presented data, allowing them to draw their own conclusions and reflect.
- Data visualization that tells a story in a convincing and understandable way for everyone, not just experts in the field.
A classic example of brilliant data storytelling was a segment of Al Gore's presentation shown in the movie "An Inconvenient Truth." Watch this legendary performance in the video below:
In the above excerpt, Gore shows a linear graph depicting the level of CO2 in the atmosphere, which is increasing at an alarming rate. The graph rises up the screen, showing an increasing amount of greenhouse gases, until finally... the graph starts to rise above the screen. Then Gore climbs onto a specially built electric lift, on which he can emphasize even more how high the level is. The audience is shocked. And that's exactly what he intended.
Another example of a great data story is the TED talk by Hans Rosling entitled "The Best Stats You've Ever Seen."
Do you want to be inspired by interesting examples of data visualization? Check out a handful of inspirations on my YouTube channel.
If you create data presentations from time to time but want to elevate their level a bit, here are 7 tips on how to create good data visualizations in the data storytelling convention:
Always focus on simplicity, readability, and clarity. Understanding the data by the audience is more important than whether the visualization is beautifully designed.
Avoid overly complicated charts and diagrams. Do you want to turn a table with eight columns and ten rows into a chart? Such a chart is unlikely to be readable. It's better to split such data into several separate charts or refrain from showing everything.
Be selective - remember that presenting data is not about showing all the data you have available, but only those that confirm your thesis and are consistent with your narrative.
Pay attention to color selection: color selection is important in data visualization. Avoid too many colors and use contrasting colors to make it easier to distinguish individual elements in the visualization.
Introduce threads sequentially, one after another. After all, you don't have to show the entire chart at once. To extract a story from it, show only a fragment first, comment on it, and then show the next fragment, and so on. This way, you can build tension, suspense, anticipation, a turning point, or a gradation of emotions.
Keep it organized. Any inequalities and asymmetries, as well as so-called information noise, interfere with reading data and distract attention from key information.
Be credible. Always make sure that the visualization is accurate and the data comes from a reliable source.
And if you want to become a master of data presentations, check out our data visualization training, which includes an advanced data storytelling module. Learn more HERE>