The big data revolution has taken on an entirely new dimension in recent years, as companies in all sectors have sought to do more than ever before with the considerable high-tech resources at their fingertips. They're gathering more information and using it to discern more actionable truths about their business than they ever thought possible.
It raises an interesting question - where did this data boom come from? What factors contributed to the rise of analytics, and will they continue in the years ahead?
One conventional belief is that the rise in analytics came about as a direct result of improved data storage technologies. As companies acquired better hardware for storing large volumes of information, not to mention also using cloud computing solutions for warehousing data externally, they became more savvy about how to work with bigger, more robust data clusters. The results were impressive.
That's certainly one explanation, but it's far from the only one. According to Information Week, storage isn't the only factor.
Olly Downs, who worked in 2004 for an early spin?-off of Microsoft Research, now serves as senior vice president of data sciences at Globys, a marketing analytics firm in Seattle. Downs told Information Week that storage isn't everything. You can have fantastic resources for data storage, but if you don't have a use for them, you're out of luck.
"[The biggest misconception is] that big data is about storage technology," Downs said. "There's a lot of emphasis on the infrastructure, which is important, but not a lot of emphasis yet on good outcomes. There are a lot of people with great large-scale Hadoop deployments wondering what they're going to do with them."
Data storage has come a long way, but so too have resources for improving data quality and analyzing information. All of the above factors have played pivotal roles.
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