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Business intelligence (BI), "big data", and analytics solutions are being deployed in an increasing number of organizations, yet recent predictions point to severe shortages in the number of graduates prepared to work in the area. New model curriculum is needed that can properly introduce BI and analytics topics into existing curriculum. That curriculum needs to incorporate current big data developments even as new dedicated analytics programs are becoming more prominent throughout the world. This paper contributes to the BI field by providing the first BI model curriculum guidelines. It focuses on adding appropriate elective courses to existing curriculum in order to foster the development of BI skills, knowledge, and experience for undergraduate majors, master of science in business information systems degree students, and MBAs. New curricula must achieve a delicate balance between a topic's level of coverage that is appropriate to students' level of expertise and background, and it must reflect industry workforce needs. Our approach to model curriculum development for business intelligence courses follows the structure of Krathwohl's (2002) revised taxonomy, and we incorporated multi-level feedback from faculty and industry experts. Overall, this was a long-term effort that resulted in model curriculum guidelines.Virhe. Määritä Aloitus-välilehdessä Title, jota haluat käyttää tähän kirjoitettavaan tekstiin. 450 Volume 36Article 23 Volume 36 Article 23 analytics, information security and privacy, e-government, and role of culture in IT. Her work has been published in journals such as

Multidimensional database technology is becoming more and more important in conjunction with data warehouses and OLAP analysis. What is still lacking is a commonly accepted formal foundation . Such a model can serve as a basis for future research and standardization. Recently a multitude of interesting proposals on this topic have been published. OLAP applications have some special requirements that do not apply to other areas of multidimensional analysis (e.g. GIS, PACS). In this paper we list requirements that a formal model and a corresponding query language must fulfill to be suitable for OLAP. We compare four approaches that come closest to our requirements. After a brief description we discuss their suitability as a formal foundation for OLAP, thus providing a systematic overview. Finally, we propose directions for further research.

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