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Predictive Modeling is a way to predict future events based on past behavior. It's a combination of statistics. Predictive Analytics helps us to make smarter decisions by choosing one path over another. Nowadays, many organizations are turning into Predictive Analytics, because the predictions of data have a very positive and massive impact on their businesses. And allow them to remain competitive in this Data world.

How does Predictive Modeling work? Analyze Data from the training window to develop model: - By using several dimensions of data from the past, develop predictive models to guess objective outcomes in the control window. Check results of the model from the control window: - Without using any information in many dimensions in the control window, check model accuracy and reliability. Predict the future: - Once you have developed the model and achieved reasonable accuracy and reliability, you can now use past data (both the training window and control window) to predict outcomes.

Industries using Predictive Modeling

• Banking: Predictive Modeling helps banks to identify fraudulent activities and helps them to capture the past predicted variables and uses it to predict future outcomes. • Manufacturing: When organizations use Predictive Modeling in their manufacturing process and production, it helps them to improve their quality. And it also allows them to make better use of machine costs, monitor the machine activities and schedule the maintenance activities. • Insurance: The popularity of Predictive Modeling in insurance is increasing day by day. The insurance sector uses predictive models to assist with everything from decisions of policy pricing to potential claims expenses. • Telecom: Based on historical data and customer profiles, it is possible for the companies to classify customers according to their likelihood of buying a product or service. It also helps them to sharpen their network. • Healthcare: Predictive Modeling uses data to help physicians to treat patients, administrators to calculate utilization and for better patient satisfaction. • Government: The government uses predictive Modeling for better decisions on social media channels. And, to analyze the response of public, of different government policies and law. • Retail: Predictive Modeling helps this sector to analyse their products.

The global Predictive Analytics market size was $ 3.85 billion and is expected to reach $ 12.41 billion by 2022 growing at a rate of 22.1%.

Millions of data are generated daily and that data comes from various sectors. Predictive Modeling helps organizations to be on top with their powerful predictions. Without intelligent business strategies, it is impossible for organizations to improve or stay in the job market. But with the help of Predictive Modeling, they can predict what they should do in the future for better outcomes.