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Real-time predictive analytics is the process of extracting useful information from data sets in real time. This is done to determine and predict future outcomes. Real-time predictive analytics does not precisely predict what will happen in the future; instead, it forecasts what might happen on the basis of certain "if" scenarios.
Real-time predictive analytics is based on a predictive model which is deployed to run in order to enable decision-making processes in real time. A predictive model is built on the basis of large amounts of data. The predictive model could be built in two ways: by a data scientist or through a streaming operational data analytics platform. The whole process involves rigorous experimentation, historical data and other similar processes. This whole process is iterative by nature. This model is then made to predict run time when a continuous stream of data is fed to it. Therefore, real-time predictive analytics enhances the customer experience and in turn helps businesses to increase earnings.