Big data goes mainstream

A new group of data mining technologies promises to forever change the way we sift through our vast stores of data, making it faster and cheaper.

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We've all heard the predictions: By 2020, the quantity of electronically stored data will reach 35 trillion gigabytes, a forty-four-fold increase from 2009. We had already reached 1.2 million petabytes, or 1.2 zettabytes, by the end of 2010, according to IDC. That's enough data to fill a stack of DVDs reaching from the Earth to the moon and back -- about 240,000 miles each way.

For alarmists, this is an ominous data storage doomsday forecast. For opportunists, it's an information gold mine whose riches will be increasingly easy to excavate as technology advances.

Enter "big data," a nascent group of data mining technologies that are making the storage, manipulation and analysis of reams of data cheaper and faster than ever. Once relegated to the supercomputing environment, big data technology is becoming available to the enterprise masses -- and it is changing the way many industries do business.

Computerworld defines big data as the mining of huge sets of structured and unstructured data for useful insights using nontraditional data-sifting tools, including but not limited to Hadoop.

Like the cloud, big data has been the subject of much hype and a lot of uncertainty. We asked analysts and big data enthusiasts to explain what it is and isn't, as well as what big data means to the future of data mining.

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