Abstract
Decision making needs more support to gain momentum with increasing trend in big data analytics. Conventionally, descriptive and predictive analytics supported the decision making, however, the outcomes of the resultant analytics is of a potentially lower one. Hence, to improve the decision making support in big data analytics, a newer technique is adopted, namely prescriptive analytics, which offers an improved advancement in predicting the probable consequences and its outcome. Best outcome is achieved using optimization techniques in prescriptive analytics that identifies the uncertainties in making the decisions better. Since optimization improves the effectiveness of prescriptive analytics w.r.t varied applications. In order to address the prescriptive analytics technique over various application and to improve the effectiveness of research over prescriptive analytics, in this paper a survey on the applications of prescriptive analytics over big data analytics is addressed. Further, the key issues in prescriptive analytics and comparisons between several applications are as of prescriptive analytics is discussed in terms of the respective techniques and evaluation over it are discussed.
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