Every day approximately 500 million messages are posted on Twitter and over 1 billion files are uploaded to Dropbox. IBM estimates that we are now creating 2.5 billion gigabytes of data every day; as much as 90% of the data which currently exists, ranging from digital pictures and videos, to social media posts and remote sensor data, was created in the last two years alone.This explosion of unstructured data, captured from system logs, multimedia files, smart phones, sensors etc., has exposed the limitations of traditional database technologies and Analytics tools which were designed to handle structured enterprise data. Companies seeking to gain valuable insights from this growing torrent of data are investing in technologies capable of powering a new generation of Analytics solutions. A wave of innovative technology spanning Software, hardware, and even entire computing paradigms are now reaching “enterprise-readiness”, and hence creating the conditions for mainstream adoption. Hadoop, in-memory computing, and cloud Infrastructure-as-a-Service are key Analytics enablers where enterprise adoption is currently limited but the potential is dramatic.
Big data, massive growth
In a recent report exploring “game changers” for the US economy, the McKinsey Global Institute estimates that the widespread adoption of Big Data Analytics in retail and manufacturing alone could contribute an additional 325bn USD to US GDP by 2020, whilst delivering 285bn USD in productivity gains in the health care and government sectors. Application software is now the fastest growing sector of the Big Data market, forecast to grow at a 56% to reach 7.4bn USD globally by 2017. One of the dynamic sub-segments is Predictive Analytics, which is forecast to reach 5bn USD over the next five years. Although many of the larger Analytics vendors are based in the US, a number of promising European companies are well positioned to exploit opportunities in the Big Data market.
