Abstract

Introduction For the last several years, Masters of Business Administration (MBA) programs have been under mounting pressure to provide to prepare their students to become the next generation of Business Intelligence (BI) workers. In a recent survey of professors from more than 80 universities around the world (Betts & Kanaracus, 2010), Barbara Wixom discovered that 43% of the respondents reported that they can't adequately teach BI courses because they lack access to the needed software, hardware and real-world problems. She also indicates that It's clear from the survey that instructors want to change the way students learn about intelligence. Professors want to provide large data sets, contemporary software tools, and real-world content within their classrooms. But, factors like high technology costs, complex maintenance requirements, and steep learning curves present insurmountable obstacles. With the present economic crisis and its repercussions on the academic environments, one of the major hurdles in offering Business Intelligence is the complex and costly computing infrastructure necessary for the software used in such courses. On the other hand, unless Business Intelligence becomes a mainstream field at schools, the shortage of intelligence related professions will continue to rise. The cloud computing, also known as software-as-a-service, delivery model has the potential to become a major force in the future of offering BI courses. After a decade of growth and adoption, the commercial cloud computing offerings came into existence and products like Amazon EC2, Microsoft Azure and Salesforce.com helped to popularize it. The concept of on-demand BI promises to make it affordable for schools to deliver quality BI instruction to MBA students. Computer Science programs were among the first to develop experimental undergraduate data mining as reported by Lu and Bettine (2003). Banks, Dong, Liu and Mandvikar (2004) report on teaching data mining as exciting addition to the curriculum at the senior/graduate level that provide the opportunity to apply computer related education to various domains and applications. Paper by Roiger (2005) presents a very good tutorial on data mining that can be used by educators as an introduction to intelligence. The typical structure of a data warehousing and data mining course in the Computer Science curriculum is well described by Fang and Tuladhar (2006) and Musicant (2006). Information systems programs at schools typically offer BI as elective (Watson, 2006). A good example of an applied BI course that is designed to appeal to the graduate students of the CIS programs as well as MBA students selecting the CIS concentration is presented by Mrdalj (2007). Specifically, the structure and components of this course focus on business aspects of data mining and data warehousing by having students learn how to answer today's BI questions. In one of the rare papers related to MBA programs, Mrdalj and Diallo (2010) present the structure and components of a BI module that is designed to appeal to students of the finance program as well as to MBA students selecting the finance concentration. In the next section of this paper we stage our proposed solution with a brief presentation of the typical computing infrastructure architecture needed for teaching BI with a discussion of possible on-premises installations. It is followed by the description of cloud computing and its possibilities in teaching BI courses. We conclude with perceived difficulties in using cloud computing as a platform for teaching BI courses. Computing Requirements for BI Courses The typical computing infrastructure architecture needed for teaching BI is shown in Figure 1. It requires a database server to host source databases as well as the data warehouse. …

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