The Big Business of Big Data

Jacob Harper  |

The flow of data in our world is growing exponentially. To be precise, the amount of data created by the world – be it every movement of the stock market , the billions of photos uploaded on Facebook, or just the daily candy sales at the Warrensburg, Ohio Git n’ Go – doubles roughly every 40 months. Currently, over 2.5 quintillion bytes of data are created every day. And the library of information gets deeper and more complex with every passing second. This collection of unthinkably giant stores of data has been given an apt moniker by analysts: Big Data.

But what makes the concept of Big Data fascinating is also what makes it maddening for the research wings of companies. Thanks to the internet, reserachers have a ton of information on their customers, information that’s theoretically valuable. But that information is so vast, complex, and constantly growing that they don’t have time to assemble it, let alone know what it even means.

A theory has begun to develop among some companies that if you get the right algorithm, if you get computers big and strong enough to not just dig through all that information that’s been stored and catalogued, you could mine Big Data your last competitve edge. And companie slike Avago (AVGO) are riding that theory all the way to the bank.

The financial possibilities of "solving" Big Data are tantalizing. And companies are starting to invest heavily in this notion. The Harvard Business Review even declared data scientist to be 2013’s “sexiest job.”

After all, a company that knows how to use its data correctly could foresee the trends in their industry, maybe wven predict the future of their entire market. Fueled by these tantalizing possibilities, data management is now a $100 billion a year biz, and shows no signs of slowing down.

So who’s betting they can turn 2.5 quintillion bytes into a seer’s ball?

AMAZON (AMZN) It’s no surprise this company every sale they make comes with plenty of information on its user base. Unlike a brick-and-mortar retail shop, Amazon knows their customers purchase history, where they live, even what they might be merely interested in based on their search history. Amazon’s current database of information, after all, is an astounding 24.7 terrabytes.

WAL MART (WMT) The giant retailer logs over 1 million customer sales an hour across its 10,700 stores and 10 e-commerce sites. In June 2013 the Bentonville, Arkansas-based big box shop snatched up Big Data start up Inkiru. Inkiru is set to work directly with WalmartLabs, Inc., Walmart’s technology arm, to help the company parse its $10 billion internet and $466 billion brick-and-mortar sales a year.

IBM (IBM) On June 26 IBM announced that they were ramping up support for their Big Data division, and that they had just finished developing software called BLU Acceleration. They’re promising this new tech will speed up data analysis seven to 40 times over. It’s a big promise from IBM, who despite a steadily rising stock over the last nine years declined for most of 2013.

MICROSOFT (MSFT) Quentin Clark, the corporate VP of Microsoft’s data platforms division, stated on July 1 that he believed that Big Data platform Hadoop is “the cornerstone of a sea change coming to all businesses.” The company is very curious about the possibilities of interpreting data at a hitherto unseen speed and efficiency. After all, succeeding at cracking Big Data could mean an edge on the search engine biz, which of course is dominated by their competitor Google (GOOG) .

NETFLIX (NFLX) Netflix famously used Big Data to ensure the success of their 2013 drama House of Cards. Netflix knows exactly what their customers watch, how much they watch, and even if they stop watching at specific points in a movie or television show, and thus Netflix had a ton of information on their users’ preferences. By cracking this data, they were able to determine that a serialized drama starring Kevin Spacey would almost certainly succeed. And they were right.

DISCLOSURE: The views and opinions expressed in this article are those of the authors, and do not necessarily represent the views of Readers should not consider statements made by the author as formal recommendations and should consult their financial advisor before making any investment decisions. To read our full disclosure, please go to:

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