In the age of big data, the world’s most successful companies will be data-driven enterprises. That is to say, data will be hardwired into their decision-making through automated processes that enable them to move with great speed and agility. To reach this level of performance, however, many businesses will need to overcome three significant challenges, which in many cases are now holding them back.   The first issue to overcome is to understanding what big data technologies can accomplish and then confidently selecting a solution. Immediately following this challenge comes the large constraint of budgetary pressures. Data volumes may be increasing exponentially but corporate spending on technology is heading in the opposite direction. IT managers are expected to do more with less, often while coping with systems built a decade or more ago that are now reaching the end of their lives. As a result, many enterprises are fast approaching inflexion points beyond which performance will suffer.

The third problem is that most businesses might not realize the breadth of the big data opportunity. They have a rigid approach to new ventures that is based on building a business use case and testing it for potential return on investment. When it comes to big data, however, there are an almost infinite number of possible use cases, many of which are unanticipated. Testing use cases for big data is like being asked to find a needle in a haystack when you’re not sure what a needle looks like – or a haystack, for that matter.

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