Visualization tools have been around for a long time. Timelines, as I've noted here before, go back more than 100 years and the hoary pie chart dates to 1801. Humans excel at interpreting data when it's presented visually compared with culling through endless tables packed with numbers in columns and rows.
This isn't just supposition. It's proven fact. Recent independent research by Mindlab International quantified how much more efficiently the human brain works when visually assessing information compared with looking at data presented in text as numbers and words. According to the study reported by the BBC, our brains use 20% fewer resources when evaluating visual as opposed to textual content. Further, individuals retained 4.5% more information with visual discovery tools compared to traditional software. Finally, among those people studied, individual productivity jumped 17% when using visual discovery software.
Yet despite this and other evidence about the benefits of analyzing data with visual tools, most business analysts rely on text-based data or the simple-minded static graphics in spreadsheets. The result is often paralysis by analysis. As Jean Francois Mourier observed, "The most commonly understood example of paralysis by analysis is when a project involves so much computer-generated analytical data that employees have no idea where to begin and where to end."
It's not just workers in the trenches who can be overwhelmed by the sheer volume of information they confront before making a decision. CEOs and other executives similarly face paralysis by analysis. Recent research by Dr. Lynda Shaw at Brunel University here in the UK revealed that top executives are literally "hiding" from those who expect a decision because they are so overwhelmed with data they can't make up their minds. Procrastination becomes their preferred mode of management.
"When we feel overwhelmed we start to delay making decisions," Shaw told the BBC.
In our big data, real-time world today, delaying a decision is tantamount to making a wrong choice. We lose competitive advantage and miss opportunities. However, if we could see the data visually, as the Mindlab study showed, we'd draw conclusions about the information more quickly and incisively. But our visual tools need to be more than Excel charts. We need more powerful, highly interactive analytic software that can display information in myriad ways that best suit the data and the analyst.
Luckily, visual discovery software has made great advances recently as the underlying analytics infrastructure, especially in-memory databases, has dramatically ramped up analytics capabilities. These new databases permit analysts to interact with data visually and instantly. As such, visual discovery tools paired with in-memory, columnar databases are the perfect combination to handle the big data deluge. With them, we're not constrained to simply believe what we see; we know it.
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