The major trend he has seen recently is an effort to pull together silos of data into a single data warehouse with feeds from all their different systems to run analytics across all the assets under management.

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The far-reaching nature of big data analytics projects can have uncomfortable aspects: data must be broken out of silos in order to be mined, and the organization must learn how to communicate and interpet the results of analysis.

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So, in one fell swoop, this story underscores two of my favorite themes: the enormous potential of big data analytics and the critical importance of tearing down corporate silos.

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By 2016, Chow hopes that GoldenSource will have assisted the majority of firms to break down data silos in a potential billion dollar market.

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The Big Data challenge requires aggregating the data across these silos for a single view of the organization.

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Yet all of this data lies buried, sitting in silos.

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Schmidt realized this company loves to talk it out, jettisoning hierarchy, business silos and layers of management for a flatter, "networked" structure where the guy with the best data wins.

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