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'''Prescriptive analytics''' is the third and final phase of [[business analytics]], which also includes descriptive and [[Predictive analytics|predictive]] analytics.<ref>Lepenioti, K., Bousdekis, A., Apostolou, D. and Mentzas, G., 2020. Prescriptive analytics: literature review and research challenges. International Journal of Information Management, 50, pp.57-70. https://www.sciencedirect.com/science/article/pii/S0268401218309873</ref><ref>{{cite journal|author1=Evans, James R.|author2=Lindner, Carl H. |lastauthoramp=yes |title=Business Analytics: The Next Frontier for Decision Sciences|journal=Decision Line|date=March 2012|volume=43|issue=2}}</ref><ref name="LustigEtAl">http://www.analytics-magazine.org/november-december-2010/54-the-analytics-journey{{cite journal|last=Lustig,Irv, [[Brenda L. Dietrich|Dietrich, Brenda]], Johnson, Christer, and Dziekan, Christopher|title=The Analytics Journey|journal=Analytics|date=Nov–Dec 2010}}</ref>
Referred to as the "final frontier of analytic capabilities,"<ref>https://www.globys.com/2013/06/gartner-terms-prescriptive-analytics-%E2%80%9Cfinal-frontier%E2%80%9D-analytic-capabilities</ref> prescriptive analytics entails the application of [[mathematical sciences|mathematical]] and [[computational science]]s and suggests decision options to take advantage of the results of descriptive and predictive analytics. The first stage of business analytics is descriptive analytics, which still accounts for the majority of all business analytics today.<ref>{{cite journal|last=Davenport,Tom |title=The three '..tives' of business analytics; predictive, prescriptive and descriptive|journal=CIO Enterprise Forum|date=November 2012}}</ref> Descriptive analytics looks at past performance and understands that performance by mining historical data to look for the reasons behind past success or failure. Most management reporting – such as [[sales]], [[marketing]], [[Business operations|operations]], and [[finance]] – uses this type of post-mortem analysis.
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