Predictive analytics is being embraced at an increasing rate by organizations that need to gain actionable and forward-looking insight from their data. Why? Companies realize that simply looking in the rearview mirror to obtain insight and make decisions is not enough to remain competitive. Companies want to better understand what actions their customers might take. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing. Some examples include customer churn analysis, predicting insurance fraud and finding patterns in health related data.
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