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Hire TalentFor anyone working in the field of data science, the possibilities that are offered by virtual reality (VR) would have already come to mind a few years ago. Fast forward a couple of years to today and we could be about to witness the next level of VR with its impact on Big Data and data visualization.
It’s not exactly the most difficult aspect of big data analytics, but often it comes down to how well data scientists are able to gain insights from available data and communicate it effectively. Further, there is a gap in the industry as there have been many instances where well-designed data models have failed to deliver meaningful insights when viewed on a dashboard. This phenomenon can be attributed to limitations in human perception itself.
Visualization is key to data science and it’s often the vital last piece of a large-scale analytics project. Gone are the days when a simple pie chart of bar graph was sufficient to get your point across. Today data is too vast and complex to tell the whole data story through simple graphs. Further, real-time visualization that’s necessary for major operations like fraud prevention requires a sophisticated system to be put in place to highlight billions of data points and correlations.
When Traditional Modeling Fails, VR Can Take Its Place
VR and augmented reality (AR) has been primarily focused on gaming and entertainment. But that is slowly changing as the technology evolves and gets adopted into different industries from engineering to science.
It can also serve a very real purpose as there is a significant limitation to the amount of data that can be absorbed from a computer screen by the human eye. So it really doesn’t make sense to have enhanced cloud processing power to keep delivering insights rapidly when the human element in the equation just can’t keep up.
The rapid adoption of big data systems like Hadoop and Tableau also make it even more important to take data analytics to the next level. VR offers immersive experiences and if internet chatter is anything to go by, data scientists are definitely craving the experiences that VR can offer them.
But it doesn’t have to stop there as this technology can also be utilized by businesses to restructure and optimize their functions visually. In fact, it’s safe to say that enterprises that incorporate big data insights to adapt their processes will be the ones that prosper and remain relevant in the marketplace.
Big Data and 360-Degree Visualization
VR technology is exciting for data scientists as it can help users immerse themselves in a digital data space with a 360-degree field of vision. Further, it doesn’t stop there as you can simulate movement in 3D to help the human mind process a vast amount of complicated insights (quickly).
In reality, it’s not something that will happen, in fact, it has already proven its worth. Defense Advanced Research Projects Agency (DARPA) has already experimented with Oculus Rift to understand big data.
Further, Goodyear has also used VR technology to perform complete simulations of racing tires based on datasets. The primary aim here was to find quick answers to questions like why the Goodyear team was losing races. Visualization enabled them to get the answer within five minutes!
This example shows that data visualization requires a major overhaul to achieve its true potential. Even though processing power and storage capabilities have significantly evolved over the years, the computer screen has remained more or less the same.
As VR and AR technologies keep getting cheaper, it can also be adopted by the wider market to achieve that same data analytical goals. Pioneer of the 3D engine, Unity Studios is also aiming to meet the needs of the big data market. This can mean huge strides towards faster and more precise data interpretation.
Current Limitations
Although bringing big data and VR together is great, developing visualizations for VR will be a new and unique challenge for developers. Not only do they have to make it highly interactive, they also have to answer data science questions. Further, they are also tasked with inspiring the human audience to come up with new research queries.
While it’s not impossible to deliver these requirements to the end user, it’s not an easy task. It will also be interesting to see how these ideas are optimized while maintaining security and speed. But the most difficult aspect of making it a real robust solution will come down to developing a model that can be highly objective and easy to understand at a human level.
That being said, Big Data and VR technologies clearly complement each other. While true greatness may be difficult to achieve in the coming year, the reward for their efforts will be immense.
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