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Alan Turing may not have known it at the time, but he was one of the first pioneers of the data science industry. Seventy years on, we're seeing the rise of the data scientist, fuelled by an increasing realisation by organisations across the world that they require new leadership if they are to get the most out of their data. This is more than just another fickle trend; a quick search on LinkedIn reveals that "data scientist" now appears in roughly 36,000 help-wanted posts.
If there's one thing big data can teach business leaders, it's this: be prepared to challenge your assumptions.
Take the case of a major US insurance broker who decided, after years in the business, to stress test the actuarial assumptions which had formed the basis of their policies up until that point. Applying big data analysis to their business model showed them that their assumptions had all been wrong -- that the policies they had been selling had been flawed all along.
Or that of a global bank, who had identified China as a key market for expansion. After months of planning and investment, their data was too fragmented to run an analysis on the return on investment of the campaign to date - so efforts continued. When the data was brought together and analysed using Hadoop, the result was startling: not only had the bank made no profit, but it had been running its Chinese expansion at a loss.
With traditional analytics methods rapidly being replaced by big data science, there is a great opportunity for businesses and governments alike.
The first chair of the Alan Turing Institute, Howard Covington has been announced. His task will not be easy: when the government-backed institute was first announced, George Osborne said it should enable Britain to "out-compete, out-smart and out-do the rest of the world" - no walk in the park. But if he plays Covington cards right, this could be a big step in Britain's big data opportunity.
Alan Turing Institute (Wikipedia, the free encyclopedia)
Source: ComputerWeekly.com (blog)