The Best Australian Science Writing 2013 by Jane McCredie

Author:Jane McCredie
Language: eng
Format: epub, mobi
Publisher: New South
Published: 2013-10-09T04:00:00+00:00

Dating

Sexual politics

Did the earth move for you?

Big Data can tell by your tweets

if you’re a psychopath:

That’s only the beginning …

Kirsten Drysdale

At the turn of the 20th century, prospectors were rugged, bearded men. They sat on their haunches by mountain streams, rattling pans, sifting through gravel with weather-worn hands in the hope of finding something shiny buried in ancient rock. Very few struck it rich.

Just over a century later, prospectors have degrees in computer science and, it’s fair to say, a rather different image. They sit on ergonomic office chairs, tapping out algorithms on keyboards running them through huge databases in the hope of finding something useful in the seams of ones-and-zeroes still so new to our planet. What constitutes gold in this new industry? A way of identifying the most persuadable voters is treasure for some, for others it’s predicting trends in criminal activity.

Data miners rely far less on luck for their livelihoods than the prospectors of old. Many earn six-figure salaries for their work – that’s pay dirt. And their fields of exploration are no ordinary geography. These people are drilling into ‘Big Data’ – the 2.5 quintillion bytes of information created daily by businesses, individuals, financial institutions, government departments, research labs and countless other organisations around the world. The potential economic value of insights hidden within this resource recently prompted the World Economic Forum to declare it a new asset class and is pushing the concept of ‘data equity’ – already well understood by web companies such as Google and Facebook – into the mainstream.

Finding those virtual nuggets is a complicated task. For a start, a big data set can include all manner of records: years – sometimes decades – of financial transactions, exchange rates, web history, air temperature, blood pressure, crime rates, personal attributes, Facebook ‘likes’, status updates, videos …

This pithy tweet from a Canadian analyst probably explains big data best for the layperson:

@SHamelCP: ‘Simplest definition of BigData ever: “it doesn’t fit in Excel”’ :)

Nowhere near. But volume is only one of the three Vs pushing the ‘data tsunami’ beyond the capacity of traditional business analysis tools and into the hands of data scientists. Velocity, or the speed with which new information is acquired and the demand to act upon it in real time, and variety – messy, ‘unstructured’ data such as images, raw text and multimedia – have, until now, also made harnessing the latent power of all this information a monumental challenge.

Hence the latest tech boom: the value of the global big data market is projected to top the US $50 billion mark by 2017, a tenfold increase from 2012. And business opportunities are manifold, ranging from storage and data management to analytical services and consulting.

Big players include established computing giants, such as IBM, Intel and HP, and traditional business-intelligence providers, while hundreds of big-data-focused start-ups have entered the fray. The rush is well and truly on.

‘It’s exploding right now, in terms of interest, in terms of activity in the vendor community – and everybody

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