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Turning Big Data into Actionable Insights

Between the growth of computing power and the rise of the Internet of Things, humanity now knows more about the world and its own systems than ever before. Faced with a large enough data set, it’s easy to find patterns that aren’t actually proof of anything. As the economist Ronald Coase once quipped, “If you torture the data long enough, it will confess.”

This collection concerns the best ways to avoid mishandling data. Contrary to some thinking, the authors feel modeling isn’t outmoded, but more useful than ever, now that it can be tested more easily against actual physical results. However, to take full advantage ofthe promise of Big Data, analysts will need to learn more about the business, and managers will need to learn more analytics. The authors of the third article argue that the best way to convey the meaning of a given model is to create a simulation that allows managers to plug in different variables and see what happens when one lever or another is pulled.

In this collection, you will learn:

  • How to avoid drawing false conclusions from your data
  • To use analytics to make better decisions
  • Why simulations are a great shortcut for handling complexity

Articles included with this collection:

Why Big Data Isn't Enough by Sen Chai and Willy Shih

Minding the Analytics Gap by Sam Ransbotham, David Kiron, and Pamela Kirk Prentice

Using Simulated Experience to Make Sense of Big Data By Robin M. Hogarth and Emre Soyer

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