In this era of information explosion, data collection is developing at an astonishing rate, but we do not necessarily understand this data. At present, big data is like an unscrupulous "beast" -- it is very complex and unstructured. Traditional 2D screen bars and pie charts have not been able to analyze big data, nor have we helped us to effectively handle large data sets. According to Forbes research, our eyes can only process 100 bytes of information per second on traditional computer screens, so we need new technologies to solve the multiple challenges posed by big data. Fortunately, virtual reality may just help us solve problems. These challenges.
Virtual reality (or VR) began to appear in some form since the 1990s. However, until recently, VR became feasible in the commercial and industrial fields. In recent years, virtual reality technology is rapidly increasing. More than one million people use Samsung VR headsets last year. VR has infiltrated video games, movies and even social media. It quickly promotes users into the 3D world. Visualization is essential for data understanding. VR allows users to immerse themselves in data in a more natural and intuitive way. We can imagine that this revolution in big data visualization could bring about considerable changes.
Here are four ways VR will change big data:
Big data will become immersive
Visualizing large amounts of data on a 2D screen is an almost impossible task, but VR offers an alternative approach. If you can stand in the center of massive data, go to a data point, and then fly to an outlier, what do you think? With VR technology, you can really move to your data, allowing you to view data points from different perspectives.
Many resource-rich companies already use VR's immersive capabilities to solve complex problems. A few years ago, with the help of Creve Maples, one of the earliest advocates of VR, Goodyear used virtual reality technology to analyze why they performed poorly in the game. Dr. Maples and his team created a virtual mitigation where Goodyear vehicles and tires were duplicated and they amplified the changes in the tire in real time, such as changes in tire pressure. This immersive experience made many important data easier to identify, and Goodyear soon discovered that it was a problem with its tires.
Analysis will become interactive
Interactivity is the key to understanding big data. After all, simulating doesn't make much sense without the ability to dynamically manipulate data. For decades, we have been using static data models to understand dynamic data, but VR provides us with the ability to dynamically process data. By using VR, you can touch data, and big data will become a tactile experience, which makes it easier to understand and manipulate.
We will learn more at a faster pace
When data is presented in a more natural and immersive manner, it is easier for humans to understand the data. This can even increase the amount of data we process in a specific time and improve data discovery. According to GE, VR has the ability to organize data in a more “same way†because 3D data is less likely to load incomprehensible facts and figures into the user’s brain.
Cross-reference data will become super-efficient
Master of Pie demonstrated their VR technology. In their presentation, they emphasized the ability of users to instantly modify data. According to a big data researcher who can test the technology, she can see four times the amount of information under "one look."
Big data is already an important part of our lives, and VR can help us reshape the relationship with big data and may enhance our data analysis capabilities. VR is making data simulating and interacting. In addition, it can increase the amount of information we can ingest and give us a better understanding of the data. As the amount of information available expands, we must find more effective techniques to analyze the data, and VR can help us do this.
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