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Simulation: Modeling Cause & Effect for Powerful Predictive Analytics

Simulation: Modeling Cause & Effect for Powerful Predictive Analytics

There are two main approaches to implementing predictive analytics: pattern recognition and simulation.

Artificial intelligence and machine learning, which generate a lot of buzz across industries, employ pattern recognition, while simulation is another, more human alternative.

Simulation is a powerful approach to understanding the causes behind business problems, predicting future trends, and recommending optimum decisions. This ebook explains simulation — where it came from, where it is headed, 5 stages in developing a simulation — and most importantly, how it makes big data useful by producing actionable predictions.

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Any industry can use predictive analytics to improve efficiencies, reduce risks, and improve revenue. Many already are. These and other fields currently benefit from predictive analytics applications: healthcare, retail, manufacturing, financial services.