Data visualization allows us to tell a story with numbers, in a fashion that our brains can instantly comprehend. However, being successful with your visualizations depends on the quality of the data utilized, the right questions posed, an understanding of the audience – not to mention, an elegant simplicity that immediately communicates its purpose.

This isn’t always easy to achieve; let’s face it, our human brains are incapable of understanding the ever-increasing amounts of raw data that are available in every segment of business today. That is why data visualization has taken such a prominent role in the analytics field; charts, tables, and graphs help our brains to process information in an easily seen and understandable fashion. In fact, research has indicated that visuals have been found to improve learning by up to 400 percent.

According to the Visual Teaching Alliance:

  • The brain can see images that last for just 13 milliseconds.
  • Our eyes can register 36,000 visual messages per hour.
  • We can get the sense of a visual scene in less than 1/10 of a second.
  • 90% of information transmitted to the brain is visual.
  • Visuals are processed 60,000X faster in the brain than text.

But in order to glean the best possible insights, several key factors must be taken into account.

Data Quality

Firstly, we must have confidence in the quality of our data. We must understand the where, when,who and why of the the raw data in order to determine meaningful and actionable insights and results.Therefore, the information management process must be closely monitored and controlled. Remember the old adage, “garbage in, garbage out”.

Solving for the Right Question(s)

Next, it is important to make sure to ask the right questions of the data. What are you attempting to discover? Are you asking too little or too much from it? How should you bin it to show emerging patterns and trends? How should outliers be handled? These are just some of the questions you should ask before you create your visualizations.

Additionally, including aspects such as comparison, performance, and change can help paint an accurate picture of your data performance. Asking the right questions will allow your visualizations to clearly point the way forward towards successful data storytelling.

Understanding your Audience

Another key issue is that you must understand your audience. Every chart table and graph tells a story, but your story must be tailored to your audience. The same data can be utilized for different purposes, for example, to improve operations or to understand customer behavior, but each of these aims would result in vastly different visualizations. Knowing who your audience will be and what they need the information to provide, makes your story applicable and engaging.

Keeping it clean

Finally, your visualizations should be appealing and consistent. Use color judiciously, make sure your typeface is clean and not too small. While creativity is great, use that creativity in the questions you ask and the insights you glean. Simple is best. Eliminate non-essential information and make sure every chart/table/ graph suits its purpose and answers the question posed or communicates the insight given.