Data visualization is the most important stage of data analytics. If you’re not uncovering meaningful patterns in your datasets that lead to insights, you may as well not have bothered with the rest of the process. Data visualization is, simply put, the best way for a business user with limited data science experience to reveal these insights. As Chi-Yi Kuan, Director of Business Analytics at Linkedin, noted in a recent interview with us, ‘In the age of big data, there are mountains of data in every company. If you don’t have effective visualization, it won’t yield a grain of insights and returns.'
An effective visualization helps users to get to the right data easily and answer a specific question visually. The human brain has remarkable pattern recognition capabilities, but the majority of people struggle to comprehend anything that they cannot visualize in some way. There are now many companies who make big money from data visualization tools looking to fill this need. However, many of these tools do not deal with the rising complexity of data sets. As the amount of data companies collect grows, data projects require an increasingly granular method of presentation to tell the full story. Today’s tools are often highly inefficient because they do not truly consider the science behind human visual perception and choose instead to focus on aesthetics - pretty charts that move about a lot but reveal very little. They cannot effectively visualize more than two or three dimensions, and don’t allow for exploration from numerous perspectives.
Poor data visualization tools are a cognitive bottleneck on the path between data and discovery. But there could be a technology set to complete turn things around: Virtual Reality (VR).
According to research firm IDC, the market for augmented and virtual reality is expected to grow from $5.2 billion in 2016 to $162 billion in 2020, with tech companies like Facebook-owned Oculus making significant advances in the consumer market. Research in VR has already yielded a number of important discoveries, particularly in areas where the primary dimensions are spatial, such as the healthcare and underground cave analysis structures. As the technology evolves, as it is only going to over the next decade, such stories are only going to become more frequent.
Immersive data visualization offers easier pattern recognition in big data sets and more intuitive data understanding. Unlike conventional data visualization models that rely on two axes in a spreadsheet, VR allows users to walk around and look at the data from multiple angles, comparing any number of different factors at the same time.
VR works because it focuses your entire field of vision, allowing you to concentrate exclusively on the objective. In early experiments, researchers found that users who interacted with the data through VR reported better retention of perceived relationships within the data than when viewing it through two dimensional data visualization tools. According to SAS software architect Michael D Thomas, we cannot process more than 1 kilobit of information per second when reading text from a screen. By being ‘present’ in the data, you can get a true sense of scale which is impossible to achieve when viewing the data on a desktop screen.
There are already a number of companies further developing the technology. Among them is Pasadena-based Virtualitics, who recently launched its product that places researcher directly into the data. It uses machine learning to help analysts determine which factors will provide the best possible mapping, which then creates a multidimensional data representation. Virtualitics also allows other colleagues to meet inside the same virtual space and collaborate on analysis of the data in real time. Alongside the launch, the start-up announced a $3 million seed round from angel investors to use developing its technology further.
According to one of the company’s founders, Professor George Djorgovski, ‘VR is intrinsically well-suited for human perception, intuition and pattern recognition, leading to insights that may be difficult or even impossible to gain through any traditional visualization technique. It is a natural environment for collaborative visual data exploration and data analytics that enables teams of users, who may be continents apart, to interact with the data and with each other in a shared virtual space.’
The possibilities offered by VR are huge, and nowhere is it more important to businesses than data visualization. The naturalistic way it allows people to interact with virtual objects, the ability it affords individuals to experience the data through all senses - touch, sound, and even smell - mean that there are many opportunities yet to be explored, and data visualization companies should start preparing.