Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud

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Using service-oriented decision support systems (DSS in cloud) is one of the major trends for many organizations in hopes of becoming more agile. In this paper, after defining a list of requirements for service-oriented DSS, we propose a conceptual framework for DSS in cloud, and discus about research directions. A unique contribution of this paper is its perspective on how to servitize the product oriented DSS environment, and demonstrate the opportunities and challenges of engineering service oriented DSS in cloud. When we define data, information and analytics as services, we see that traditional measurement mechanisms, which are mainly time and cost driven, do not work well. Organizations need to consider value of service level and quality in addition to the cost and duration of delivered services. DSS in CLOUD enables scale, scope and speed economies. This article contributes new knowledge in service science by tying the information technology strategy perspectives to the database and design science perspectives for a broader audience.

论文关键词:Cloud computing,Service orientation,Service science,Data-as-a-service,Information-as-a-service,Analytics-as-a-service,Big data

论文评审过程:Available online 29 May 2012.

论文官网地址:https://doi.org/10.1016/j.dss.2012.05.048