Predictive Analytics is a branch of advanced analytics that uses historical data, statistical algorithms, and machine learning techniques to predict future outcomes or trends. By analyzing past events and identifying patterns, Predictive Analytics provides insights into what might happen in the future, helping businesses and organizations make data-driven decisions to mitigate risks, optimize operations, and seize opportunities.
Predictive Analytics goes beyond data description and diagnosis to forecast future probabilities with a reasonable level of reliability. The process encompasses several steps, including data collection, data cleaning, statistical analysis, model building, validation, and deployment. Predictive models are used in various domains such as marketing, finance, operations, healthcare, and others to forecast demand, predict customer behaviour, identify potential risks, and optimize processes. It's an integral part of a broader spectrum of analytics that also includes descriptive analytics (what happened), diagnostic analytics (why it happened), and prescriptive analytics (what should be done). By utilizing Predictive Analytics, organizations can anticipate outcomes and trends to gain a competitive advantage.