Companies are using data visualisation to communicate with their employees, their stakeholders through their annual reports for example, their partners, and their marketing departments use them to communicate with media and customers, they are used in white papers, they use it to tell stories of complex events, associations, occurrences, projections and more in a single graphic representation.
The biggest users of data visualisation today, though, are marketing departments. That scenario will likely change as more companies begin using it for discovery, analysis and operational alerting, says Mervyn Mooi, director at Knowledge Integration Dynamics (KID).
However, it is in collaboration that the greatest benefits of data visualisation in the near future should be realised. It is a trending topic at universities around the world, from Australia to the US, and being investigated for a number of purposes, including emergency management.
In fact, in Australia in 2011 at The University of Melbourne, one student used the software engine that powers a computer game to improve emergency management by incorporating real-time spatial information into a 3D virtual environment that improves the results obtained from what-if scenarios run through the program.
It included collaborating with numerous external sources from the Internet, geographical information systems (GIS), direct and remote sensing, emergency management and support systems, hazard analysis, modelling and warning systems, and wireless sensor networks.
Visualisation offers numerous business benefits that these trends seek to harness:
* It is simpler to comprehend visual information, when properly presented, compared with tabular reports;
* Analyses are sped up as many indicators can be bunched into a single display, which can be made interactive on the spot – for example, for use in what-if analyses;
* Visualisation lends itself to sophisticated presentation of information, for example, with comparisons, time series analyses and so on; and
* It considers, once again if properly done, all the important factors in the algorithms used to produce the information.
Many organisations have yet to implement and realise the full benefits of visualisation yet the concept is not new. It is experiencing a reinvigorated hype cycle, much as big data is experiencing.
Visualisation was dominated, and still is to a large degree, by standard business intelligence (BI) and data mining technologies in the past. In fact, the underlying algorithms to produce the output presentations are much the same, except embedded now in more sophisticated reporting and query tools.
Visualisation of data and information for presentation has been with us for decades and now the only difference is that it has evolved from a rather manual or semi-automatic process at best to a much faster automated process with new visual representation methods.
Visualisation for discovery, analysis and event alerting – three areas pegged by the analysts as future growth areas – is also not new. Most mining tools today can be programmed to execute discovery and analytical algorithms, including pattern recognition and entity, trend and event relationship analyses.
Self-directed analyses depend on what the outcome of each previous step was – which can be modelled in mining or standard reporting processes and programs. The final outcome is, of course, unknown or unpredictable until all the factors in the algorithm have been traversed through the sampled data.
One such past tool was NetMap, which would show patterns, trends and relationships in insightful ways, using symbols, colours and sounds. It also featured full drill-down capabilities into the underlying data.
When users pack all of that capability into tools that allow collaboration then businesses get a whole new set of capabilities that were unachievable in the past.
Mines, for example, can use visualisation because it allows them to overlay geological survey data with mine schematics to visualise ore reserves. It allows them to do what-if analyses based on recovery rates and they can create 3D models of data of underground reservoirs, for example, that they can use for operational purposes.
In the case of mines they can overlay publicly available information, from across the Web, that allows them to quickly see relationships between different data that exposes new information previously unknown.
That is entirely different from trend analyses where many factors are known beforehand. With geological survey data of ore veins, layout schematics, shaft and face locations with external reservoir data used to create 3D models mines can use data visualisation to aid planning and strategies, just as the University of Melbourne student used it to improve emergency unit response times.a
