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You’re at a new building site. A line of trucks back up and dump an assortment of raw materials on the lot. Sheets of plywood amid the girders and beams. Tangles of plumbing bits and electrical fixtures. Screws and nails and fasteners sprinkled over the top. It will take your crew days to manually sort the pieces before the build can begin. Big data is like that–which is why data visualization is more important than ever before.
A huge pile of data can consume and obstruct the project roadmap, despite being exactly what the project needs to be its very best. Until it’s sorted, connected, and applied, data is merely stuff and things. Data visualization, powered by user experience and interaction takes the materials and makes a home. It gives your business the proof it needs to deliver on a vision.
Most understand better when they can see. But screens full of unsorted numbers don’t connect any dots. Spatial relationships are everything. Graphs, charts, and diagrams do good work, but adding a time factor through animation or video yields even deeper understanding through sequence and narrative.
When relationships between data points are clearly laid out, the information tells a story, providing invaluable context alongside solutions. And enhancing this story in three-dimensional space via mixed reality data visualization, transforms complicated information into a memorable immersive experience.
A visual representation is a good start. But sometimes you want to drill down on a certain variable, change the view, or test the outcome of a hypothetical condition. (Check out this interactive animation of population mobility) When you can reach into the information display to zoom in, move pieces, or pull elements together, you’ll end up with a pin-pointed, custom view of the right data.
In this way, the graphic representation is no longer something you artificially absorb. It becomes a two-way visual language. When visual analytics are applied to enterprise security, for example, the results can mitigate catastrophic, personal information consequences. In real time, the software can trace the digital fingerprints of a malicious intrusion, and display which parts of the system are compromised. An investigator can then drill down, identify, and address the problem, eliminating or reducing the impact.
Extracting useful information means being able to recognize patterns at the base level, all the way up to more superficial layers. This is the capability artificial intelligence offers — at light speed. AI can identify which variables in the raw data stream are most relevant and able to ground subsequent data. Then it helps decide on the best way to assemble them visually to build clear understanding from bottom-to-top.
However, handling massive amounts of information and then delivering it in a graphic format takes a lot of bandwidth. That’s why dedicated gamers have special graphics processing units in their computers. Data visualization companies such as Graphistry offer cloud technology, so that even sophisticated graphics and animation don’t require the user to have expensive hardware, just an ordinary browser.
Today’s data visualization specialists produce graphics that are far more sophisticated than pie charts, scatter plots and bar graphs (although those tried-and-true formats still have seats at the table). But a bar graph that needs thousands of bars? There’s the rub. Software based on artificial intelligence fuels accessibility for data visualization, but still butts up against an automation barrier.
For this reason (and because someone has to create visualization platforms), universities offer data visualization coursework and degrees to help build a better launchpad for expertise.
Data visualization courses draw from a range of disciplines. Students learn how to approach, consolidate, and apply raw data–embedding digital skills into overall communication expertise. Both Purdue University and Parson’s School of Design offer data visualization degrees.
Companies across industries need people who can take information and transform it into solutions (aka, innovators). And these solutions are not only effective, they can also be quite beautiful. In fact, the Kantar “Information is Beautiful” awards were created in 2012 to celebrate data-as-art. Visual appeal not only helps data absorption, but, more importantly, its retention. People remember beautiful things.
As much as you rely on your mobile devices, the fact remains: phone screens are tiny. Complex graphs and charts, even some more intense infographics, don’t show well. Which is why augmented reality, and the increasingly available AR hardware, offers a viable solution. AR glasses, or standalone headsets empower multi-layered data, creating a data experience.
Walking around 3D content to view it from any angle solves the 2D screen perspective limitation. AR platforms can also discover your geographic location and incorporate your preferences into resultant information displays. For instance, if an app knows that you’re allergic to peanuts, it can layer green or red lights over food products in real-time as you walk down the aisle of a real-life supermarket.
Removing the outside world completely, VR tracks your head (and sometimes body) movements, putting you in the middle of an entire visualization environment. Also, it ups the level of interactivity by adding collaboration. Several people can share the same environment, regardless of their geographic location.
When multiple people and/or parties can all interact with visual data, it’s much easier to facilitate productive discussion and decision-making. Enabling internal and external teams to experience the impact of the same data creates a tremendously effective sales tool and more tangible means to realize success metrics.
In a data-saturated market, finding some sort of proof is easy–but finding the most empirical evidence is an art. Whether it’s a small decision about a product shipment, or a broad decision about company innovation, you need the right data, as well as the best vehicle to share that data.
When you reach the top of the mountain of raw data and see the market landscape in 3D, then you can decide how your business will solve for and design the best version of itself.
