In the last month I’ve had notifications of 30 events in 9 countries on some aspect of the big data ‘revolution’. My sceptical view might be that there’s more money in organising conferences on the topic at the moment than there is in delivering value from the concept.

When starting a futures exercise, one of the most helpful exercises is to start by looking backwards. If you want to understand say big data in 10-20 years then start at least 10-20 years back and see how we got to where we are today. Some futurists prefer to start at least twice as far back as they want to look forward arguing that we will see as much change in the next x years as we have in the past 2x years. In some areas they may have a point.

One value of the exercise is that everything has a history. You will uncover examples of what we now call big data that stretch back before the term was coined.

I’m pleased to say that someone has done a good job of that in a clear and lucid style. Victor Mayer-Schonenberger of the Oxford Internet Institute and Kenneth Cukier of the Economist have written a handy book called simply ‘Big Data’. I confess to finding books co-written by an academic and a journalist as a useful genre, balancing rigour with readability.

The tone is that of messengers not messiahs for the topic and this helps what is a coherent narrative illustrated by lots of examples that show how we have got to where we are today, before looking at plausible futures for the near term.

What I found particularly helpful was an analysis of the use of big data to find out ‘what’ is happening rather than the focus on ‘why’ it’s happening. I took the chance to look at some of the claims that have annoyed me over the last couple of years and armed with the what/why difference it’s clear that claims that big data solves ‘why’ problems are based largely on ignorance (IMO).

The strength of the book is the clarity of its structure with chapters looking in an enthusiastic but balanced way at messy, correlation, datafication, value, implications, risk, control and next as distinct aspects of the topic.

I confess that I don’t always agree with the authors’ analysis. Life would be boring if I did, but the scaffold they provide to build a personal perspective on the topic has been a help to me in ordering my own thinking.

The chapters on risk and control have significant public policy issues as well as ethical challenges at their heart.

I think that the book is very timely and to be welcomed. It would be interesting to speculate on a second edition in 2015 and what will have changed. My guess is that a chapter on unintended consequences may be helpful when we have more evidence of what works.

If you are on the supply-side or potential user of the topic, read this book. It will make it more likely that you will set expectations in an intelligent way and deliver value rather than become a victim of the hype.

Data, data everywhere and not a drop to drink... cheers

About the author

Chris Yapp is a technology and policy futurologist. Chris has been in the IT industry since 1980. His roles have spanned Honeywell, ICL, HP, Microsoft and Capgemini. He is a Fellow of the BCS and a Fellow of the RSA.