Data visualization is more than pretty graphs to illustrate a PowerPoint presentation: executed well, it can present even the most voluminous and complex datasets in a way that pretty much everyone can understand at a glance. That’s supremely useful within organizations where decision-makers may not have the time or patience to parse through mountains of data.
But as organizations wrestle with ever-greater amounts of data, there’s a growing need for a more refined look at data visualization—including a careful consideration of the tools in use, and whether they truly fit an organization’s needs. So writes Forrester analyst John Brand in a recent corporate blog posting about visualization’s “changing landscape.”
According to Brand, factors driving the evolution of data visualization include the aforementioned increasing volumes of data, more complexity in data relationships, and users’ growing ability to interact with data instead of merely viewing it. “Gamification” also plays a role, he added:
“We’re now seeing much more emphasis on introducing “game play” as part of data visualization. This can be as simple as including some level of interactivity to allow the user to drill down into information, but it can also go to the extreme of integrating real-time, multi-player simulations. These are common in highly regulated or life-threatening work environments where attention spans may mean the difference between life and death.”
The rise of “cognitive computing,” in which devices such as tablets and smartphones absorb enormous amounts of data about us and what we’re doing at any given moment, is the last factor contributing to the evolution of data visualization: such devices provide an exceptionally rich vein of information, which in turn can be modeled in all sorts of ways.
Those machines will also take more of a role in deciding what sorts of visuals best represent the data in play, Brand wrote, although people will still have the ability to interact with the data once the software has done the foundational work. The challenge is choosing the right visualization tool and strategy to fit a company’s needs.
“Generally enterprises choose a tool—or set of tools—and then implement their data visualization solutions based on the capabilities of those tools,” he continued. “It’s very rare to see organizations giving much consideration to identifying the very best way of representing each individual data requirement and then finding specific solutions to fit.”
But that consideration is apparently key. Brand advises that CIOs (and other tech pros tasked with deciding an organization’s visualization strategy) examine how their organizations process and present data, “and ask themselves and others ‘Is this the best way to represent this data? Can we do something radically different to increase the impact and value of this information to the business?’”
In addition, companies that specialize in data visualization sometimes offer courses in visualization techniques; Brand advises that CIOs and other employees involved in data give those courses a serious look.