Intelligence series: How can rail get value from Big Data?

Big data denotes data that has either a high velocity, a high variety or high volume. For instance, data collected from sensors in real time, data combining text, images and sounds on social media, and the dozen exabytes (10^18 bytes) of data contained in Google’s data centres, are typical examples of big data. The storage and processing of big data requires specific architectures, and advanced analytic techniques must be employed for their exploitation, enabling predictive analytics, the optimisation of complex systems, and the use of data mining to discover new trends and correlations.