Analysis of large volumes of business data enables users to make more informed decisions more quickly, improving companies’ reactions to events and possibly improving company performance, says global research and advisory firm Gartner analyst Kurt Schlegel.

Displaying data analysis in visual format improves users’ ability to spot trends and patterns in data.

“Visual representations enable people to discover meaning, insight and associations in data sets, which, in turn, enable them to make informed decisions” he says.

“The human visual cortex is designed to recognise patterns. However, by combining natural human intuitive pattern recognition with the power of big data processing and analysis, users will be able to derive significant insight from data. It is the combination of visual interpretation and computational algorithms that is powerful,” says Schlegel.

For example, chess grandmaster Garry Kasparov defeated the software giant IBM chess machine Deep Thought in 1989, but was defeated by the improved Deep Blue chess machine in 1997. Deep Blue required human intervention between games to be able to defeat Kasparov, who defeated the pre- vious iteration in 1996.

“But this also means that, since 1997, an amateur chess player and this single machine can defeat the world’s best chess player. This is the power of big data analytics – not removing people, but augmenting our capabilities,” enthuses Schlegel.

However, the manner in which data is presented has a significant effect on its usefulness.

Intuitive representation is important and removes the need for significant training so that users can filter out irrelevant information and obtain relevant information. Intuitive representation and user interfaces also drive adoption.

“Representation is not so much about monitoring changes, but more about discovery. Using visual representation and manipulation to discover meaning in the data set is important to understand what interventions will be effective and also leads to better analysis,” notes Schlegel.

However, monitoring dashboards are necessary and should be used alongside analytics visualisations to provide the monitoring and reporting that companies require, as well as to measure goals and report on actual performance, he adds.

Further, using large, visually prominent dashboards to provide common visualisations for groups of users in a company, instead of relying only on single desktop dashboards, effectively provides a common metric that informs group performance.