Here’s the session outline (see video summary at the end of this post)
Petervan introduced the session saying that we have some of the worldwide biggest thinkers on the subject of Big Data as igniters to this session. And boy! he’s right.
Immeditely after, Sean Park (Founder, Anthemis Group) suggested that what we’ll talk about will seem pretty much like magic 🙂 He proceeded to introduce a fictional character, Henry, born in 2004 that we followed through his life and the way Big Data technology impacts him. Some spooky things in there, such as that analytics will be able to predict his age of death.
Sean was followed by Michael Chui (Senior Fellow, McKinsey & Company) who shared the results of the McKinsey study on Big Data. Big data matters for financial institutions where the factory is the data center. One insight from Michael is that companies will need to prepare for Big Data by nurturing the right analytics skills.
Larry Ryan‘s (Chief Technologist Financial Service Industry, Hewlett Packard) main message is that we need a whole new set of technologies to deal with Big Data. He used Zenga as an example of how they understand their customer’s behavior using analytics.
Jeff Jonas (Chief Scientist, IBM Entity Analytics Group and an IBM Distinguished Engineer, IBM) introduced an interesting metaphor – puzzles – to explain Big Data and how analytics are linked to computer power. He first made the audience actually works on some puzzles to understand this fully. It turns out, and it is counter-intuitive, that the more data you have the less computing power you need, as the data starts in fact aggregating (like a puzzle). Beautiful and playful demonstration.
Jeff was followed by Amir Halfon (Senior Director of Technology, Capital Markets Global Financial Services, Oracle) who provided some definitions about Big Data and shared his perspective as to how these apply to today’s challenges, particularly regulation. He then proceeded to explain how financial institutions can start their analytics today.
David Campbell (Technical Fellow, Microsoft Research) described the Big Data challenge in one sentence: turning signal into value. In numerous ways. And he warned that Big Data will become vital for many companies’ survival.
Francis Martin (Head of Business Intelligence, SWIFT), introduced one practical tool illustrating Big Data – the SWIFT Index, correlating SWIFT network traffic with economic activity and GDP. He showed (and actually made people work it on their own) how this can be used as an analytical and predictive tool.
We then had Michael Driscoll (CTO, Metamarketsgroup) who also provided some useful and pragmatic advice. His key points are: ” Data is sexy!” and “Stop throwing away customer data!”
Finally, as Petervan said, we had the cherry on the cake. Michael Ouliel (Founder and CEO, Ripples HLS Group) talked about some REALLY Big Data – quintillions of data. He awed everybody. These are the volumes processed daily by the intelligence services. He then logically concluded about the importance of using semantic tools and techniques to figure out and spot important data meanings.
Below is the video with the key points of each talk.