Sybase® IQ Powers Predictive Analytics
In an age of more demanding customer expectations and increasingly aggressive and adaptable competitors, organizations are rapidly moving from reliance on business intelligence (BI) tools that provide a snapshot of the past to those that provide an accurate picture of the present and a prediction of future trends. This branch of data mining known as predictive analytics is the latest front in the battle for the advancement of BI tool capabilities, as customers demand not only an understanding of what happened in the past, and why, but also want to be able to accurately predict what is going to happen in the future.
Predictive analytics is a subset of advanced analytics and data mining that is concerned with predicting future events via mathematical models. The central element of predictive analytics is the predictor, a variable that can be measured to predict future behavior. For example, an insurance company is likely to take into account potential driving safety predictors such as age, gender, and driving record when issuing car insurance policies. A collection of such predictors is combined into a predictive model, which, when subjected to analysis, can be used to forecast future probabilities with an acceptable level of reliability. Businesses that rely on predictive modeling follow a process that involves collecting data, developing a statistical model, and then making predictions which enable validation or revision of the model.