Data visualization: Adding color to the numbers to tell a story
To gain a competitive advantage in the digital economy, businesses are racing to glean insights from the mountains of data and information they generate. Insights are the foundation for transformative change within a business, but enterprises are bogged down with sheer enormity of data produce these days and unable to identify patterns quickly and accurately get to the insights and actions that enable them to win.
Data visualization is indispensable for cutting through the noise and communicating a concise narrative. Data is simply a collection of numbers until it’s transformed into a story. To make a story more memorable, help your readers visualize it by giving it color and picturesque detail. This also applies to data storytelling: the relationships, trends and patterns you perceive in data is what you want to communicate to your audience.
Among all the various ways you can distinguish different data elements such as shape, size, or motion, color is the most immediately eye-catching. This is because humans have evolved to perceive rich color palettes, with different hues, saturation and brightness evoking a wide range of meanings and emotional associations. Reds are often associated with alarm or vibrancy and can deliver a highly visible punch to a message, while earth tones like piney greens and sapphire blues can convey a sense of calm and tranquility. This can turn a once bland data visualization into a transformative experience.
In the words of data visualization grandmaster Edward Tufte, “graphical excellence is that which gives the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.” Practitioners emulating Tufte will deploy color in their visuals to better help users understand relationships and trends in data more swiftly and intuitively.
But how does a data team accomplish graphical excellence, especially when there isn’t design experience within the team? The answer is to first employ tools which present complex data in visual forms that stakeholders are already used to. Flexible tools with broad ranges of chart and graph styles provide a great starting point for conveying complex findings and highlighting emerging patterns more clearly. These include everything from basic pie and bar charts to sophisticated representations, such as spiderwebs, ring charts and word clouds, which can be installed in dashboards or as reporting interfaces in other applications.
Next, enhance your visual by brushing it with different strokes of color and manipulating the size and location of objects to encode quantitative values. Choosing the right hues takes careful consideration. For example, avoid using the entire spectrum of the rainbow or bright neon, because this can overwhelm viewers. This notion is discussed in Serial Mentor’s “Fundamentals of Data Visualization” through the use of a qualitative color scale. With this, specific colors should look clearly distinct from each other while also being equivalent to each other. When reflecting a positive or negative correlation to your data, it also may be tempting to use the same shade or hue, but this will confuse readers. Using muted colors for low values and more vivid colors for higher values will be most effective. In addition, play with each color’s lightness and note that too much variation can overwhelm readers.
An illustration of data visualization at its best is the below example produced by AthenaHealth, which exhibits an in-depth report of healthcare in the city of Lowell, Massachusetts. What makes this visualization so captivating is the cohesive balance of both text and color throughout the report and the powerful story it can tell. The color-coded map is a breakdown of Lowell’s ethnic makeup, showcasing how the city has witnessed a major cultural transformation in recent decades. For example, the cluster of yellow dots in the upper right shows how Hispanic immigrants have moved into the upper outskirts of the city after the “white flight” phenomenon of the 1960s. Clusters of red in the lower middle denote Asians settling in newer developments in neighborhoods downtown.
What this visualization showcases is that in order to keep the entire community healthy, AthenaHealth had to invest in understanding and accommodating all of the various cultural communities that resided in the city.
Ultimately, because humans are visual creatures, conveying information through this lens makes large swaths of data more easily understood and deciphered. As seen above, applying the right color and texture to your data visualization models captures the attention of your audience quickly and engages the viewer on an emotional level. By sticking to these core principles, you will bring visualization and storytelling to life and make your data truly memorable and actionable.