TY - JOUR
T1 - Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs
AU - Gupta, Babita
AU - Goul, Michael
AU - Dinter, Barbara
N1 - Gupta, Babita; Goul, Michael; and Dinter, Barbara (2015) "Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs," Communications of the Association for Information Systems: Vol. 36, Article 23.
Available at: http://aisel.aisnet.org/cais/vol36/iss1/23
PY - 2015/1/1
Y1 - 2015/1/1
N2 - 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.
AB - 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.
KW - Analytics
KW - Big Data
KW - Business Intelligence
KW - Curriculum Development
KW - Model Curriculum.
UR - https://digitalcommons.csumb.edu/cob_fac/10
UR - http://aisel.aisnet.org/cais/vol36/iss1/23
M3 - Article
VL - 36
JO - Communications of the Association for Information Systems
JF - Communications of the Association for Information Systems
ER -