Effectively Conveying Data Through Visuals: The Art of Data Visualization

As business intelligence tools and analytics solutions have evolved, marketers have gained access to a tremendous amount of raw data and information. Conveying this sophisticated data, however, can be challenging.

Unless you do a good job of being clear and concise, the data you work so hard to gather will essentially be useless. The key is understanding the art of data visualization.

The Value of Data Visualization

Did you know that 55 percent of big data projects fail? This means more than half of all projects serve no purpose at all. While these failures can be chalked up to a number of causes, the reality is that many come up short because they don’t take the “last mile” into account.

The “last mile,” which refers to the stage during which insights are presented to key decision makers, is arguably the most important aspect of any data project. However, despite the importance of this stage, data visualization is rarely given the attention and time it deserves. Unfortunately, this is a death sentence, as data cannot be properly explained with generic interfaces, boring charts, and lackluster illustrations.

Enhancing Your Approach to Visualization

“A data-driven culture is key to every business’ success,” writes datapine, a leader in business intelligence. But it’s not enough to merely have a data-driven culture. If you want to convey the right takeaways and properly leverage the information you’ve gathered, this data must be presented in a visually pleasing and enticing manner.

Let’s briefly review some key concepts and tips that will allow you to give data visualization the attention it deserves.

1. Understand the Golden Rule. In the world of data visualization, there’s a golden rule that consists of three words: Keep it simple. Honestly, that’s it. If you’re going to live by a single rule when investing in data visualization, this is the one you want to follow. By keeping everything simple, you’ll be effective and successful.

What does simple look like, you may ask? Well, the answer is largely subjective and situation-specific. As a rule of thumb, simple means excluding anything that doesn’t serve the purpose of making the takeaway clear. In other words, nothing should be included “just for the hell of it.”

2. Select the right format. The second thing to think about is the data visualization format you’re using. This is where things can get really confusing if you don’t know what you’re looking for. After all, there are scatter charts, histograms, bar charts, heat maps, line graphs, timelines, tables, pie graphs, intervals, and dozens of additional options.

The key is to understand the best and proper use of each format. For example, tables should be used when there are multiple categories with both numbers and names. Bar and column charts are ideal for showing the distribution of data over a select period of time. Line graphs are good for showing the movement between different data points (such as stock prices). Pie charts are commonly used when you want to show how one element consists of different sections and proportions.

While it takes time to learn about the different uses of each format, the time you invest learning about these various nuances will help you in the long run.

3. Guide the user with colors. One of the best tools you have at your disposal is color. However, it must be properly leveraged. When used incorrectly, color can actually serve as a distracting force. With that being said, what does proper usage of color look like?

Well, it involves a concrete understanding of the color wheel and how primary, secondary, and tertiary colors interact with each other. This allows you to visualize the harmony and balance of colors. For more information on color theory, just check out this easy to read guide.

4. Use headlines and text to complement. While the visualizations you choose should do all the talking, it’s sometimes necessary to guide the viewer with a few simple words. Just remember to keep it simple.

Don’t Give Up on the Last Mile

When it comes to projects that are based on data and research, you have to remember that you’re dealing with a marathon, not a sprint. And the key to winning a marathon is finishing the race--you can’t give up on the last mile and expect to win. While you may have succeeded throughout the first 25-plus miles, the last mile can make or break your results.

The same is true with data projects. While the hard part is collecting and interpreting the data, the last mile–delivering the information in a visually pleasing manner–is equally important. Use the tips mentioned in this article and finish the race strong!