Big data 2.0: Mining the deep learnings of data-driven projects

The problem with big data analytics is that there’s simply too much data to process. Simply stuffing more and more of it into bigger and bigger repositories exposes the inability of businesses to extract the expected value from it. But help may be on the way, according to Tony Velleca, CIO of IT services firm UST Global. “There is more data than people know how to deal with,” says Velleca. “Businesses are sitting on a mess of structured and unstructured data, but the amount of value they expected to get out of that data is far less than they are actually getting.” But don’t despair: “What I think we’ll literally see over the next 12 months is what we call deep learning,” Velleca says. Keeping pace IDG Enterprise’s 2015 Big Data and…


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