Why couldn't tech predict the US election results?

Such sentiment analysis, however, comes with a heavy workload and also requires mathematical models. "There are three ways to make improved predictions – a better model, better data, and more data," says Jeremy Perlman, VP Europe for Trifacta, which helps RBS, Santander and PepsiCo analyse data. "The problem is that data created on social media and the web is expanding at a ridiculous rate, so machine learning will be critical to making better predictions at massive scale." Since computing power is increasingly exponential with the birth of super-computing in the cloud, the need to analyse more and more data shouldn't be a major hurdle. "Computational devices can very effectively, with high precision and rapidly, gather millions of tweets, posts or similar and run sentiment analysis – to understand likes and dislikes," says Jepson.