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Why would users need Linked In to figure out their networks for them?

The site already had an address book importer that could pull in all a member’s connections.

Much of the current enthusiasm for big data focuses on technologies that make taming it possible, including Hadoop (the most widely used framework for distributed file system processing) and related open-source tools, cloud computing, and data visualization.

While those are important breakthroughs, at least as important are the people with the skill set (and the mind-set) to put them to good use. Indeed, the shortage of data scientists is becoming a serious constraint in some sectors.

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“Once they have data,” says Dan Portillo, who leads that team, “they really need people who can manage it and find insights in it.” If capitalizing on big data depends on hiring scarce data scientists, then the challenge for managers is to learn how to identify that talent, attract it to an enterprise, and make it productive.Goldman continued to refine how the suggestions were generated, incorporating networking ideas such as “triangle closing”—the notion that if you know Larry and Sue, there’s a good chance that Larry and Sue know each other.Goldman and his team also got the action required to respond to a suggestion down to one click. Patil, and Jeff Hammerbacher, then the respective leads of data and analytics efforts at Linked In and Facebook.) But thousands of data scientists are already working at both start-ups and well-established companies.Something was apparently missing in the social experience.As one Linked In manager put it, “It was like arriving at a conference reception and realizing you don’t know anyone.

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