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Big Data Industry to Hit $114 Billion by 2018

As billions of people around the world pump massive amounts of information through the internet every day, business (and the NSA) are going to need solutions to parse their data. Some of the smartest ...
Big Data Industry to Hit $114 Billion by 2018
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  • As billions of people around the world pump massive amounts of information through the internet every day, business (and the NSA) are going to need solutions to parse their data. Some of the smartest people in the world are now working on so-called “big data” problems, and the market for such technology is now expected to skyrocket in the coming years.

    Market research firm ABI Research today estimated that worldwide spending on big data will hit $114 billion by the year 2018. That’s up from an estimated $31 billion that will be spent on the industry this year.

    “We estimate that in big data initiatives salaries account for about half of the current spending, with the other half allocated to vendors’ products and services,” said Aapo Markkanen, senior analyst at ABI. “What we’re now seeing is quite significant overspending on salaries, as organizations turn to data scientists and other specialists in order to leverage big data in the first place. Similarly, a good share of the money is spent on the associated professional services, which have sprung up to assist firms that are data-rich but skills-poor.”

    According to ABI, that $100 billion won’t be going to waste. The firm predicts that data innovation will come quickly over the next few years. Database analysis improvements will, ABI says, improve efficiency, while machine learning will improve analytics overall.

    “Machine learning and its application in advanced analytics is one area that will make both the public and private sectors data-savvier than anything we’ve seen so far,” said Dan Shey, practice director at ABI. “Big players such as IBM and HP are understandably moving to this direction, but at the same time we can also see analytics startups, like Ayasdi and Skytree, that have machine learning in their very DNA. Eventually, such innovations will put analytics within any domain expert’s reach. At that point, data will stop being ‘big’ again.”

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