Get more Value From Big Data With Visualisation-Based Data Discovery Tools

The problem is that big data alone is not necessarily suited to delivering on this promise in a manner that is easy to digest. In fact it can be an overwhelming environment that is of little use to employees and managers. It is for this reason that significant growth of 30% annually is predicted by Gartner in the area of visualisation-based data discovery tools over the next two years.

This type of solution can turn torrents of esoteric and unwieldy data into the kind of package that enterprise staff will find eminently usable. It also makes it possible to meld data from a variety of sources to deliver even deeper insights. Information harvested from social media, video interactions, log files and many other platforms can be combined and assessed in parallel, unearthing the kind of findings that might otherwise be obscured and ensuring that businesses can get the best possible value from their big data service.

In the digital age and with big data rising to prominence, this approach is simply inadequate, because being able to assess and unlock the potential of vast stores of information is a task too great for in-house analysts. An Intel report recognises that the volume, variety and velocity of information in a big data environment can be such that the challenges posed with be insurmountable for some companies.

Big data is generally unstructured and a survey from IBM found that only a quarter of the IT professionals questioned had the means to effectively analyse information in this state, such as that presented to them in the form of voice and video files. A little over a third were able to get a handle on streaming data and harness a portion of its underlying value. In terms of the time pressures that are put upon businesses by big data, if there is no way to wring relevant insights from information in real time then further inefficiencies will prove to be a hindrance rather than a help. A further pressure is emerging in the wake of mobile and remote working becoming more common, since businesses need to democratise access to information and analytical tools so that a more geographically diffuse workforce can still collaborate and operate effectively.

That sense of democratisation of data analytics is something which should be seen as key in this case, because the idea is not only to make it faster and easier to analyse data from multiple sources, but to make this a process which does not require a specialist set of skills. Rather than relying on the work of a small group of professionals, it is faster and more sensible to give every employee the ability to generate usable and relevant visualisations of data that has been analysed. This self-service approach means that productivity will be improved just as costs are being reduced, which means the main challenges of big data are no longer so significant.

Real time data analysis is a top priority and something which is made possible through these tools, along with the ability to create presentations and reports quickly and make them as engaging as possible through the inclusion of interactive elements. Data and the tools to manage it also need to be accessible to staff whether they are at their desks or out in the field and using a smart device. Collaboration should be achievable in a secure, safe environment that facilitates sharing, so that team members can make valid contributions and work towards a collective goal.

When it comes to the actual interface used in visualisation-based data discovery tools, this has to be something that is intuitive enough to require minimal training to master, as well as enabling deeper insights into the data. Touch optimisation is also important, particularly with tactile displays not only featuring on smartphones and laptops but also on a growing number of enterprise-oriented laptop computers and desktop workstations.

Although the volume, variety and velocity of information in a big data environment can feel overwhelming to the uninitiated, the reality is that with visualisation-based data discovery tools it is easier to wrangle these three under control and ultimately convert them into value for the company.