Predictive analytics

Predictive Analytics

Predictive analytics (/prɪˈdɪktɪv ænəˈlɪtɪks/) is a branch of Advanced Analytics that uses historical data, statistical algorithms, and machine learning techniques to predict future outcomes based on historical data. The goal of predictive analytics is to forecast what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessment.

Etymology

The term "predictive analytics" is derived from the ability of these methods to "predict" future outcomes based on historical data. The word "predictive" comes from the Latin "praedicere", meaning "to foretell", and "analytics" is derived from the Greek "analytikos", meaning "able to analyze".

Related Terms

• Data Mining: The process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
• Machine Learning: A type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed.
• Statistical Analysis: The collection, analysis, interpretation, presentation, and modeling of data.
• Forecasting: The process of making predictions of the future based on past and present data and most commonly by analysis of trends.
• Risk Assessment: The identification, evaluation, and estimation of the levels of risks involved in a situation, with an aim to determine what actions (if any) are necessary to reduce the level of risk.

Applications

Predictive analytics is used in a wide range of disciplines, including healthcare, marketing, finance, and operations. In Healthcare, predictive analytics can be used to predict patient outcomes, identify high-risk patient groups, and optimize treatment plans. In Marketing, predictive analytics can be used to forecast customer behavior, optimize marketing campaigns, and improve customer retention. In Finance, predictive analytics can be used to assess credit risk, detect fraud, and optimize trading strategies. In Operations, predictive analytics can be used to forecast inventory demand, optimize supply chain management, and improve operational efficiency.

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