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Biggest Problem with Big Data: Search… or Find?

It doesn't matter the size of the business, inefficient data search and find can be costly.

With the continuing exponential rise of data volumes one of the biggest problems that doesn't get an airing is the continuing challenge, not of munging, prepping, and analysing, but a far more basic one – searching, and then finding. Never mind 'you can't manage what you can't measure' – if a business can't find the right data in the time available, it will use the data that it can find – and that may lead to outcomes ranging from less precise decisions to out and out poor decision-making.

According to a landmark 2012 McKinsey research study showed that 19% of the average work week is spent unproductively searching and gathering information. McKinsey found that social technologies, which create value by improving productivity could potentially contribute $900 billion to $1.

3 trillion in annual value across four sectors they reviewed: Consumer packaged goods, retail financial services, advanced manufacturing, and professional services. McKinsey estimated that the average interaction worker spends 28 percent of the workweek managing e-mail and nearly 20 percent looking for internal information or tracking down colleagues who can help with specific tasks.

A statistic by Outsell showed that an engineer's time spent searching for information has increased 13 percent since 2002. And a survey by SearchYourCloud revealed that workers can take up to eight searches to find the right document and information they need.

One final stat: An IDC research paper has shown that "the knowledge worker spends about 2.

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