Humans love lists. Whether its chuckling their way through 27 Cats Who Think Theyre People or guffawing at the Top Ten Cats Who Look Like Dictators, I think we can all agree, people need to stop looking at cats on the Internet.
Thats not to say lists minus the cats dont still have a place. Especially lists with useful information. Theyre easy to digest, and whilst not entirely definitive, they do at least serve to give a decent overview on a given subject. Distilling all the information on a chosen subject down into something you can devour whilst having a cup of tea whats not to love?
As an agent for a speaker bureau, such lists are particularly useful when speaking with clients, advising them on who they should have speak at their next event. All of which takes us nicely on to my Top Five Big Data Speakers. A subject as MASSIVE as Big Data, summed up neatly in the views of just five speakers, with all others mercilessly cast aside like Chairman Meows unwanted salmon chunks. You can ignore all other Big Data bods, because this is it, these are the five:
Kenneth Cukier quite literally wrote the book on Big Data. His book is called Big Data. Kenneth is not one for nuance. What Kenneth does do brilliantly is describe just what big data is and how it will change our lives. He sets out the social and business landscape, highlighting the opportunities that exist as well the pitfalls. Kenneth shows how its not a case of data suddenly being present that wasnt there before, but rather that we now have the tools able to process it and reap the benefits. The collective knowledge of everybody, rather than one person, can be a tremendous good, so the key becomes how best to administer this knowledge.
Dan Cobley is the Former MD of Google in the UK and Ireland. Think of Google and you think of data, so who better to show how to farm such masses of information than Dan? Google Flu Trends is often held up as a great example of how data can be used in a positive way. By collating peoples search terms Google was able to predict flu outbreaks of flu far quicker than the Centers for Disease Control and Prevention. Early detection is key to controlling the virus, so being able to know where its likely to strike is a massive boon to the agencies in charge of staving off a potential epidemic.
Tim Harford is best known as the Financial Times Undercover Economist. Tim can turn his hand to various subjects, one of which is Big Data. Funnily enough, Tim takes a slightly different stance to Dan Cobley and points out the potential pitfalls of big data. Tim again points to Google Flu Trends, but this time highlights its frailties and the dangers of correlation over causation. Google Flu Trends dramatically overestimated a severe outbreak after years of successful predictions.
This could have been down to a number of reasons, but it serves to highlight the dangers present if you fail to understand what is behind a correlation, rather than just acknowledging a correlation exists. Obviously the recent election proves just how wrong interpretations of data can be. Whilst Tim isnt a skeptic of big data, its useful to have a voice out there that doesnt forget the key tenets of statistical analysis, rather than ignore them purely because the data set is larger.
David McCandless isnt a big data expert per se, but rather a data journalist and information designer. His book, Information is Beautiful is a wonderful collection of graphics, where David makes sense of huge swathes of data in a fairly easy to understand diagrams. From these its far easier for the man or woman on the street to see connections and patterns that might easily have been missed, or not even analysed in the first place, if they were merely located on a boring old spreadsheet.
David Coulthard – It may seem slightly strange to position a formula F1 driver as a Big Data aficionado, but given the huge amount of data used in the sport, theyre actually very well placed to comment. Ive seen David Coulthard interviewed on the role data has to play in modern Formula One. He pointed out the transition in the sport from intuition and gut feel, to one that now relies hugely on data.
Todays F1 cars have over 40 buttons on, allowing the driver to self-engineer as they go. Data is gathered from hundreds of sensors on the car and over a race weekend hundreds of gigabytes of data will be stored. The data is analysed by pit crews in real time as well as by engineers back at the team factory. Its the real time reactions to data that are the most exciting and crucial to success.
David draws the parallel between Formula One and business, highlighting how success is all about harnessing data and intelligently analysing it. In todays world it really is all about data and not about gut feel.
