Big Data: A big problem with big solutions for big money? (29 October 2013)

Big data is the often misused term for a collection of data sets so large and complex that it becomes difficult to capture, curate, store, search, share, transfer, analyse, visualise and, actually, pretty-much anything unless you’re a real expert (mathematician) with expert tools.

This trend to ever-larger data sets is due to the vast amount of additional information that can be derived from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data. ‘Big Data’ gives us the opportunity to find correlations to, for example: spot business trends, determine quality of research, prevent diseases, detect terrorism, combat crime, and determine real-time road traffic conditions.

Since the predicted amount of internet traffic in 2013 is 670 exabytes does this contain ‘big data’ sets or just lots of it? Does it present us with a problem or an opportunity? Will we be able to help the world with it? And will be able to make big money out of it?

Book today to find out more, examine what ‘Big Data’ really is, gain further insight into how big data is created and how it can be used to all our advantage – and perhaps disadvantage – and to ask very difficult questions of our world-renowned speaker at the Real Time Club dinner and debate on Tuesday 29th October 2013.

Professor Peter Grindrod CBE CMath FIMA

Pete is currently Professor of Mathematics at the Mathematical Institute in the new Wiles Building at the University of Oxford.

He was previously Director of Innovation and Knowledge Exchange, Professor of Mathematics and its Applications at the Department of Mathematics and Statistics and the director of the Centre for the Mathematics of Human Behaviour (all at the University of Reading).

His current work is focussed on specific data rich segments including: Big Data Analytics and commercial and public applications; Digital Society (P2P communications networks, media, advertising, cyber security); Big data analytics within neurodynamics; Smart energy and smart grid and behavioural change; and modelling big data challenges underlying social media, human behaviour and social norms.

Pete’s work is mostly through industrial collaborations and – amongst others – he works with Cignifi Inc., developing behaviour-based credit referencing; with CountingLab Ltd. looking at customer centred insights for the retail and supply sectors; with Scottish and Southern Energy plc. and others in the energy sector for the analysis of customer usage rich-data; and in the digital marketing sectors with Bloom Media.

Pete has been a Council Member for the Engineering and Biology and Biological Sciences Research Councils. He is an independent member of the MOD’s Defence Scientific Advisory Council and received his CBE in 2005 for services to mathematics R&D.