Data is at the center of most challenges facing our industry today, with business drivers such as new regulations, aggregated risk management, and deep customer insight all having critical data management implications. The term Big Data has become a common way to describe this, and while some of these challenges are associated with large volumes, it isn't really the size of the data that's at issue. I'd argue that at this point we know how to handle large volumes: use shared-nothing architectures that scale horizontally on commodity hardware. The trickier problem has to do with a different "V" of Big Data - variety - and it is that aspect that I'd like to focus on.
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