Isn’t this the truth? ‘Because sometimes things happen to people and they’re not equipped to deal with them’.
It is the kind of pop-lit wisdom fiction readers love. And I say that with real authority knowing 17,784 Kindle users in Australia highlighted that sentence from the second book in Suzanne Collins’ runaway success trilogy, The Hunger Games.
How do I know this? Because Amazon knows this. And it knows because it collects petabytes of data on every move a Kindle user makes.
Of course, Amazon isn’t just collecting the data; it is using that data to understand reader proclivities and create more efficient and effective ways of creating wealth through book sales.
Global giants like Amazon, Google, Apple, and Facebook have been early adopters and pioneers of big data. It is big data analytics that tells me what friends I should connect with, what movies I might like to download and increasingly, who I might vote for. Big data delivered the names of the 69 million people who voted in 2008 to the 2012 Obama campaign together with the relatively small portion of Republicans or Democrats who might be willing to change their vote.
Big data can provide unexpected insights. For example, using big data, Walmart in the US discovered there is a clear correlation between hurricanes and an increase in sales of beer and raspberry pop-tarts. Now, I’m not sure about you but I can understand a run on torches, batteries and other survival products as a hurricane looms large on the horizon. But pop tarts?
Australian corporates are starting to make the investment too. The Commonwealth Bank, Coles, Woolworths and Target are among early big data investors.
But is this big hype? It is clear the venture capital barons of Silicon Valley have re-aligned their investment priorities from seeking the new social media platform to enterprise mobility, storage and data analytics. McKinsey & Co estimates there is $700 billion in value in big data waiting to be unlocked for both corporate and consumer.
With an eye on the future, leading Australian management consulting firm, the Nous Group, recently invested heavily in strategic analytics capability. When advising clients on how to extract value from the increasingly large data sets, Nous asks three questions.
Firstly, what is the problem that needs solving and what are the data sets currently available or potentially available to help solve it? Secondly, which algorithms and tools can help solve the problem? The strategic analysis of big data needs to start with the basics including network analysis, decision theory, machine learning, natural language processing, Bayesian statistics and multi criteria analysis, to name a few.
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