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Selecting appropriate cloud solution for managing big data projects using hybrid AHP-entropy based assessment

机译:使用基于混合AHP熵的评估法选择合适的云解决方案来管理大数据项目

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摘要

Today technology that learns from data to forecast future behavior of individuals, organizations, government and country as a whole, is playing a crucial role in the advancement of human race. In fact, the strategic advantage most of the companies today strive for are use of new available technologies like cloud computing and big data. However, today's dynamic business environment poses severe challenges in front of companies as to how to make use of the power of big data with the technical flexibility that cloud computing provides? Therefore, evaluating, ranking and selecting the most appropriate cloud solution to manage big data project is a complex concern which requires multi criteria decision environment. In this paper we propose a hybrid entropy method combined with Analytical Hierarchical Process (AHP) to select appropriate cloud solution to manage big data projects in group decision making environment. In order to collate individual opinions of decision makers for rating the importance of various criteria and alternatives, we employed usability analysis using the proposed hybrid AHP-Entropy method.
机译:今天,从数据中学习以预测个人,组织,政府和整个国家的未来行为的技术,在人类进步中起着至关重要的作用。实际上,当今大多数公司争取的战略优势是使用新的可用技术,例如云计算和大数据。但是,当今动态的业务环境在如何利用云计算所提供的技术灵活性来利用大数据的功能方面给企业带来了严峻挑战。因此,评估,排名和选择最合适的云解决方案来管理大数据项目是一个复杂的问题,需要多标准决策环境。在本文中,我们提出了一种混合熵方法,结合层次分析法(AHP)来选择合适的云解决方案,以在群体决策环境中管理大数据项目。为了整理决策者的个人意见,以评估各种标准和替代方法的重要性,我们使用了提议的混合AHP-熵方法进行可用性分析。

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