Analytics

5 strategic tips to avoid big data failure

Following are five strategic tips for avoiding big data failure. In many cases, the advice pertains to any data management project, regardless of the size of the data set. But the advent of massive data stores has brought with it a particular set of pitfalls. Here’s how to increase the chances that your organization’s urge to mix large data pools from disparate sources is a success.

Big data success tip No. 1: Make big data a central business tenet

Rearden Commerce CTO Phil Steitz succinctly sums up the single most important driver of big data success: You must integrate analytics and data-driven decision making into the core of your business strategy.

“If ‘big data’ is just a buzzword internally, it becomes a solution looking for a problem,” Steitz says.
For Reardon Commerce, whose e-commerce platform leverages big data and other resources to optimize the exchange of goods, services, and information between buyers and sellers, the concept of “absolute relevance” — putting the right commercial opportunity in front of the right economic agent at the right time — is key.

“It is an example of this kind of thinking originating and centrally driving strategy at the top of the house,” Steitz says.

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