BI technology has grown in this era of information intelligence and still emerging with new and advanced solutions. One of the most promising approaches in the BI domain is prescriptive analytics.
To understand the concept of prescriptive analytics, firstly one should understand and relate it with descriptive and predictive analytics since prescriptive analytics is closely related to both of them. While descriptive analytics aims to stipulate insight into what is already occurred and predictive analytics peeps into model and forecast that can occur, prescriptive analytics is meant to look for the best solution among several options, given the known parameters. Prescriptive analytics might also advice decision choices for how to take benefit of future chances or alleviate a future risk, and describe the consequences & insinuations of each commitment alternative. In reality, prescriptive analytics may continually and automatically process current data to enhance the accuracy of predictions and provide better commitment alternatives.So to visualize the prescriptive analytics concept, refer the following figure:
Enhancements in the speed of computing and the development of complex mathematical algorithms applied to the data sets have made prescriptive analysis possible. The particular approaches included in prescriptive analytics are mainly as follows:
To summarize, prescriptive analytics is the top management level activity that helps to determine higher level decisions and hence add and improve business value.