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Predictive analytics is a branch of data analytics that uses statistical techniques, machine learning, and data modeling to predict future outcomes based on historical and current data. By leveraging techniques like regression, classification, and time series forecasting, predictive analytics answers questions like, "What is likely to happen?" It plays a critical role in various fields, such as predicting customer churn in businesses, forecasting demand in supply chains, or estimating risks in insurance underwriting. The predictive power stems from the use of algorithms that analyze patterns and trends, enabling decision-makers to anticipate future scenarios and prepare accordingly. For example, in the insurance industry, predictive analytics is used to estimate the likelihood of claims based on policyholder demographics, historical data, and external factors. By doing so, insurers can better assess risks and optimize their pricing strategies. Why Other Options are Wrong:
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