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Why Big Data Isn’t Enough

  • Research Feature
  • Read Time: 13 min 

There is a growing belief that sophisticated algorithms paired with big data will find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and potentially risky, as spurious correlations and “noise” may lead analysts astray.

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How to Manage Risk (After Risk Management Has Failed)

Over the past decade, a number of the world’s respected companies have collapsed. A factor was these companies’ approach to risk management. Two different views have evolved on how risk should be assessed. The first — the frequentist view — is based on historical data. The second, or Bayesian, considers risk to be in part a judgment of the observer. Many measures are being deployed to prevent future crises — a shift from frequentist to Bayesian risk management should be part of this effort.

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New opportunities for data analysis

  • Blog

“We’re rapidly entering a world where everything can be monitored and measured,” Erik Brynjolfsson, director of the MIT Center for Digital Business, said in an article in The New York Times.

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