Data analytics platforms are always changing with their functionalities expanding and becoming more accessible with each passing year. 5G promises to bring analytics to our cars and other consumer products, but what about virtual reality (VR)?
VR is the latest frontier in the ‘what’s new in business tech’ space. The technology is becoming more and more streamlined and accessible, and as such, opens up new possibilities in the analysis and presentation of data. So it is worth taking a look at what VR can do for analytics in the future, and vice versa.
VR promises to transform data analytics platforms by changing platform functionalities, and how we interact with their data.
When we view data through data analytics platforms, it’s usually via a 2D screen that gives us a ‘back to front’ perspective. It is a nice perspective to have, but virtual reality technology can improve our perspective on data trends and patterns. VR technology can take that 2D presentation of data and put it in a 3D space. This will transform the way we see and analyse data because seeing data in a 3D space immerses us in a way that 2D cannot.
What is truly exciting about data presentation and visualisation with VR tech is multi-dimensional analysis. At the moment, we are using our sense of sight to analyse data, but what if we could use other senses, like hearing? For example, the significance, subject and location of data could all be relayed through sound.
One of the biggest advantages of any data analytics platforms is sorting data and presenting it for analysis. However, 2D screens only provide a set limit of options to view data – for example, pie charts and Venn diagrams. While these options are fine for sorting data, they are quite limited in comparison to the plethora of options offered through VR technology.
Virtual reality technology uses several technologies like smart mapping, NLP and machine learning to find patterns and present them in a virtual environment, which can then be customised by users. Using VR tech with data analytics platforms expands the amount of data available for analysis.
Data analysis often requires collaboration between different team members. This can be challenging to do with collaborative and communication tools, but VR is the perfect tool to work with others. Virtual reality provides a perfect virtual space that can be shared with different team members when they are using data analytics platforms.
Even better, people can share their virtual space, even if they are separated across large distances.
While we have talked about VR tech being incorporated into data analytics platforms, we have not yet addressed data analytics technology being incorporated into VR tech. It may be possible to add new dimensions to a company’s data set by collecting biofeedback data.
Data analytics, sensors and VR devices can track a user’s brain wave activity, heartbeat, and how they are feeling using visual and auditory signals. This data would be very useful in the medical field, but also in other areas, like VR training that can improve performance, accordingly.
Admittedly, it will be some time before we see virtual reality technology being incorporated into data analytics platforms. However, the prospect of interacting and manipulating data streams in a way that feels more natural than a mouse and keyboard is quite an exciting thought.
Furthermore, it’s also important to have your finger on the pulse of the industry and be aware of the latest technological developments so that we are ready to incorporate them into our service offering, as soon as it’s feasible to do so.
While VR technology and the merging of data analytics will take some time, there is still much value to be drawn from data analytics. With the right technology, businesses can reap tremendous benefits in the form of real-time insights.
Certain branches of analytics, like on-demand data analytics platforms, can provide companies with the opportunity to analyse data in real-time, and even collaborate with the data scientist team. So, while VR has yet to be incorporated into analytics, there is still much to gain from current analytics systems.