
Ask any Statistics/Probability/Math Question
Finally, last but not the least the reason for predictive analytics is to Act which is obtained by rendering business intelligence and considering analytics to be actionable.

Objective - Act
To minimize risks and optimize value in managing complex workforce and sourcing, business intelligence plays a very critical role. Apart from benchmarking and reporting on transactional data, there are other things which are required to make sensible business decisions. For making the data fit for analysis the data should be cleansed and normalized, after which on the basis of statistical analysis, decision points are provided. In order to make decisions, business analytics uses the data, and then performs quantitative and statistical analysis, which is followed by predictive modeling. With the help of analytics fully automated decisions can be driven or it may also be used as input relating to human decisions. Most of the business finds predictive analytics to be a magic trick and are not eager to apply it in business. For this reason predictive analytics has not been so much popular in some of the organizations.
It becomes important and necessary to predict the future to make decisions. This is because the decision makers can then adjust credit lines, determine which customers are going to stay or not etc. Future events and outcomes are predicted by analyzing patterns that are found in current transaction data, historical data, and even survey data. To facilitate competitive advantage, predictive analytics acts as a transformational technology to make proactive decisions. The difficult and complex business questions can be answered very well with the help of predictive analytics. One can be confident about the decisions and results obtained from predictive analytics because predictive analytics makes good use of the sample of data and predicts and forecast future behavior. Through mathematical models the future events are predicted by predictive analytics which is a subset of advanced analytics. Predictor which is a variable measured for predicting future behavior, is the most prime element in predictive analytics. Pricing analysis can be performed through predictive analytics where the optimal prices that customer's wants to pay for products and services are predicted by building predictive models, and in this way revenue can be maximized. The demand for predictive analysis is highly vigorous for managing and handling vast amount of data and where the numbers of business users may vary.

Gaining Strategic Insights
There are strategic and deep insights that are present in business. So it is important to know about the thinking of the customers and how they operate, to make out how market performs, and also the response of the customers should be known. Strategic insights which help in reducing wastage of marketing costs and maximizing opportunities for revenue should be considered, so that business can enjoy the advantage of competitiveness. Predictive analytics is deployed mostly for actions than understanding. The operational decisions for every customer can be predicted with the help of scores of the predictive model. Strategic insights can also be gained if a gander is taken into the patterns and rules that are implanted in predictive models. The most precious asset is the data. The reason is that data represents a history or a record of the company and also the customer's interaction can also be known. With predictive analytics the experiences of the companies are considered and are mined, and thus predictions can be made for every customer. One can own it if one predicts it.
Thus enterprise can be developed through predictive analytics. So it is promising and helpful in the business for competing, growing, enforcing, improving, satisfaction, learning and acting.

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