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Predictive analytics deals with prediction of future trends and probabilities. It is based on data mining.
The predictor is the main thing in predictive analytics. In predictive analytics predictor is defined as a variable which is used for the measurement of future behavior prediction. As an example can be cited in this regard . Example: Age, driving records ,gender etc. are the predictors of safe driving of an insurance company. In a predictive model all these multiple predictors are combined for analysis purpose. And with the help of this future probabilities are forecasted and the results are highly reliable. Predictive Modeling deals with collecting data, model formulation, which is followed by prediction and model validation. There are numerous applications of predictive analytics, marketing, genetics, economics etc.
It's Importance:
Not only is predictive analytics used for evaluating the present and the past but also it is used for making future prediction. Predictive Analytics utilizes some of the following methods:
 Neural networks
 Time series analysis
 Game theory etc
It has become very important in making decisions of our daily lives. The growth of predictive analytics occurs as more and more data are collected.
The following are the seven reasons for which we require Predictive Analytics in today's world:
 Satisfy
 Compete.
 Act
 Enforce
 Learn
 Improve
 Learn
 Grow
Predictive Analytics in the Future:
The importance of predictive analysis will gradually increase as more companies open up to the idea of using predictive analytics for the growth of business.
A New Phase of Enterprise Evolution:
Data based on Applied Organizational Learning Enterprise is a very effective and strategic asset that helps to represent the history of the interaction between the organization and the customers. For making strategies ,the customer's response is required. Customer's response include outright defection, credit default, faulty product complain, purchase decision ,act of fraud, and acquirement. A company or an organization can excel if it uses predictive analytics. It is with the help of organization's experience that predictive models are generated. The procedure of creating a statistical model based on future behavior is termed as predictive modeling. It relates to data mining and is used to forecast trends and probabilities. There are many predictors which make up the predictive model .The predictor are factors influencing future results and behavior. For example in case of marketing for prediction of future sale customer's purchase history, age etc acts as predictors. Recency can be taken as an example, the value will be higher for more recent customers. The predictor is actually the response predictor, due to recency the response for highly ranked customers will be greater.
