Training tomorrow’s big data analysts

Big data is about to become big business, but only, say Suzy Moat and Tobias Preis, if we can train enough data analysts and alert managers to its growing importance.

Technology is becoming ever more deeply interwoven into the fabric of society. Our interactions with the internet and other large systems that support our transport, our shopping activities and much more are generating an avalanche of data, documenting our behaviour at an unprecedented scale.

According to computer giant IBM, the world is churning out 2,5 quintillion bytes of data every day. (In US, Canadian and modern British usage a quintillion is 10^18).

Analyses by the McKinsey Global Institute underline the benefits business may reap from these data sets by gaining new insights into how their customers are behaving now and how they may behave in the future. Their projections point to a need for 190,000 more workers with analytics expertise and 1,5 million more data-davy managers by 2018 in the US alone in order to realise these gains.

Data was once used primarily as a historical resource to look back on events. As humans, however, we constantly use the “historical data”we have collected through our own experience of the world to try to predict the future behaviour of others – for example, when others will be most likely to use the roads, causing traffic, or whether a previous business partner can be trusted in the future to deliver on time.

The vast amount of detailed, real-time, large-scale data we are now collecting is making it possible to automate, improve and extend these predictions by applying computing power to detect relevant patterns that a human brain alone would not have been able to find.

Every day, over one billion search requests are answered by Google. In a recent study, we exploited the global breadth of Google data and uncovered evidence that internet users from countries with a higher per capita gross domestic product (GDP) tend to search for more information about the future (Preis, Moat, Stanley, Bishop, Scientific Reports 2, 350 (2012), Figure 1). Our results suggest that there may be a link between online behaviour and economic decision-making around the globe.

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