Data visualization, including a more specific area called visual analytics, comprises a group of technologies and techniques that allow people to explore data, then reveal and convey valuable insights otherwise obscured within generally complex data. We help you create better data visualizations.
Currently, these visualization tools are widely used from enterprise management to scientific research, finance, health-care, government, law enforcement, journalism and advocacy, to name a few. They’re used to work with data both within organizations as well as to communicate data-based facts out to key audiences or customers.
The professional conversation about data visualization can sound daunting at times, in part because the tools are so broadly adaptable and some ideas they hinge on can be a bit abstract. But don’t let that prevent you from considering how they can benefit your organization.
The computer science academic R&D sub-community (worldwide) has pretty much single-handedly envisioned and built the data visualization industry. That work has been invaluable in creating the current tools. But the scope of the innovation, in our opinion, has been limited because the R&D focus has been almost exclusively on the data-through-visualization component. Granted, some software has one or a few helpful communication features. But those alone aren’t enough to ensure that resulting visualizations will be highly effective at conveying their message clearly.
Some visualization viewers may disbelieve the data, or be suspicious of the intention behind a visualization. Also, those responsible for creating visualizations are forever unsure about the actual impacts that a visualization may have on people’s attitudes, behaviours or thoughts. That likely means they’re relying too much on just experience or gut instincts to know what approach may or may not be effective. These uncertainties interfere with visualizations’ effectiveness to communicate.
This is where social science needs to step up. The part before data is what we’d call a measurement model. And the part after visualization is a communication effects model. Both models are firmly based in empirical, peer-reviewed research. These two components can be measured, statistically modeled and visualized. (Did a light just go on?)
Effectively, this provides an end-to-end understanding and hard proof that operational data patterns have specific impacts or outcomes. At the end of the day, we can measure and prove the effects that each type of visualization and each data pattern has towards making a good business decision. Also, the data-informed/driven communications that corporations have with their customers/clients/suppliers/regulators — which imbed or comprise visualized data — will be more clearly understood, more helpful, and better appreciated.
That may sound like Nirvana that you can’t achieve overnight. In the meantime, our job is to guide you, strategically, in the right direction toward a tangible, results-oriented visualization end-state that’s optimal for your organization.
At the core of our thinking is the principle that, without exception, every data visualization communicates a message. Of course, all visualizations do contain specific data or information, but we argue that even the most technical scientific data visualization has at least one vital core message — even if such a message is implicit or understandable only by a small, specifically-trained audience.
To be clear, our company doesn’t build visualizations for clients. We can recommend plenty of smart firms and bright people to do that.
Vividdata Visualization works with organizations to develop pragmatic, achievable strategies to become more effective with data visualizations. We also design and deliver custom primary research to ensure that visual analytics systems and approaches to data visualization convey the right messages, to the right people, at the right time.
