By Guy Harrison
Predictive Analytics-sometimes referred to as Predictive Data Mining-is a branch of Business Intelligence that attempts to use historical data to make predictions about future events. At its simplest, predictive analytics utilizes statistical techniques, such as correlation and regression, which many of us have encountered in college or even high school. Correlation analysis determines if there is a statistically significant relationship between two variables. For instance, height and age are highly correlated, while IQ and height are very weakly correlated. Regression attempts to find an equation between the two or more variables, so that you can predict one from the other.
More complex mathematics-including multivariate techniques (correlating many variables at once), non-linear methods, fuzzy logic and even neural networks-are used to generate more complex probability trees and create more complex predictions.
These sorts of techniques have been commonplace in the social sciences for a very long time; but, it's only relatively recently that they have found practical application in the business world. To read more of Harrison's Applications Insight column, go to the July e-edition of Database Trends and Applications magazine.
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