Until recently big data was focused on processing massive amounts of simple, flat data. But now, there is a growing need to fuse complex data that comes from both inside and outside of organizations. This evolution is driving the need for new, less expensive and more intelligent analytic frameworks to make better business decisions.

For many years, to support business analytic needs, IT departments invested substantial time and money to pre-process data from various internal data sources into data warehouses and data marts. With the addition of big and complex data this approach is proving to be too slow, too inflexible and with a total cost of ownership (TCO) that has exploded. Additionally, data warehouses struggle to integrate data from outside the enterprise. The warehouse approach is broken for businesses that need better, faster analytics.

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