How Business Intelligence Can Influence the Delivery of Excellence in Botswana Accountancy College (BAC)

Authors

  • Ronald Chikati School of Computing and Information Systems, Botswana Accountancy College, Private Bag 00319, Gaborone, Botswana

Keywords:

Data warehouse, business intelligence, excellence, data mining, data analytics

Abstract

In today’s turbulent and ever changing environment, every business small or large is struggling to remain competitive and to manage the growing amount of data being generated from a number of existing (legacy) systems. Organizations have to align their business processes with their available information technology (IT) infrastructure to beat competition. In the tertiary education landscape, Botswana Accountancy College (BAC) could exploit the business-IT synergy through implementing a data warehouse strategy. Data warehousing can consolidate and unlock actionable information from the huge deposits of data lurking in the organization. Strategic decision making would be based on available accurate, subject-oriented, past and current information. With a data warehouse (DW) in place, BAC could have a unified view of its organizational performance; it is able to check on performance measures and become more agile to provide superior services to customers than would happen with any other tertiary institution at the moment. DW can support all decision making information needs for all potential end-users at strategic, tactical and operational levels. We argue that this type of business intelligence will propel BAC to become a center of higher education excellence. Results of study showed a high level of readiness for BAC to benefit from the business intelligence that could be derived from a data warehousing strategy.

References

Boar, B. “Understanding data warehousing strategically,“ in R. Barquin, & H. Edelstein (Ed.). Building, using and managing the data warehouse,1997, pp 277-299.

Porter, J., & Rome, J. ” Lessons Learnt from a Successful Data Warehouse Implementation,” Cause/Effect, 1995, pp43-50.

A. Perkins. “A Strategic Approach to Data Warehouse Development “. Visible Systems Corporation, 1997

A. Perkins. “Critical Success Factors for Data Warehouse Engineering Part 1”. TDAN.com, 2000

P. Lehmann & J. Jaszweski. “Business Terms as a Critical Success Factor for Data Warehousing “. 2000

Topic Overview: Business Intelligence November 21, 2008, Forrester report.

J. G. Zheng. Project: IT Lecture Notes, Topic: “Business Intelligence and Analytics: A Comprehensive Overview. “ August 2019.

Chang, P., & Cheng, P. “Transformaing corporate information into value through data warehousing and data mining.” In Aslib Proceedings, vol. 50(5), 1998, pp.109-113.

Berson, A. S. Building Data Mining Applications for CRM. New Delhi: Tata McGraw-Hill, 2002

Bingi, P., Sharma, M. K., & Godla, J. “Critical issues affecting an ERP implementation.” Information systems management, vol. 16(3), pp. 7-14, 1999

W. H. Inmon. Building the Data Warehouse, 4th Edition, Publisher: Wiley, 2005

Guan, Nunez, & Welsh. “Institutional strategy and information support: The role of data warehousing in higher education.” Campus-Wide Information Systems vol. 19(5), pp.168-174, December 2002.

Solomon, M. D. “Ensuring a successful data warehouse initiative.” Information Systems Management, vol.22(1), pp. 26-36, 2005

Daniel, D. “The Secret to Successful Business Intelligence: A Top-Notch data Warehuse.” Internet: http://www.cio.com/article/151601, 2007 [June 10, 2018].

Akkermans, J., & Helden, A. “Vicious and virtuous cycles in ERP implementation: A case study of interrelations between critical success factors.” European journal of information systems, vol. 11(1), pp.35-50, 2002

Ballard, C., Farell, M., Gupta, A., Mazuela, C., & Vohnik, S.” Dimensional Modeling: In a Business Intelligence.” USA: International Technical Support Organization, 2006

Brown, T. “Data Warehouse Implementation with the SAS System. Dallas,” TX: SAS Institute Inc, 2007

Chenoweth, T., Corral, K., & H., D. “Seven key interventions for data warehouse success.” Communications of the ACM, vol. 49(1), pp.114-119, 2006.

Ranjan, J. “Business justification with business intelligence.” The journal of information and knowledge management systems, vol. 38(4), pp. 461-475, 2008

Sammon, D., & Finnegan, P. “The ten commandments of data warehousing.” ACM Digital Library, vol. 31(4), pp. 82-91, 2000

Chen, L. D., Soliman, K. S., Mao, e., & Frolick, M. N. “Measuring user satisfaction with data warehouses: an exploratory study.” Information & Management, vol. 37(3), pp. 103, 2000

Chenoweth, T., Corral, K., & H., D. “Seven key interventions for data warehouse success.” Communications of the ACM, vol. 49(1), pp. 114-119, 2006

CXP Group. “Business Intelligence, Big Data and Analytics.” SITSI® Research Cluster 2018.

Report 2018. “Business Intelligence Trends for 2018.” eLuminous Technologies Pvt Ltd, 2018

Marrow, G. “Business Analytics & Intelligence: An Introduction and Considerations for Getting Started.” Durham County White Paper, 2018.

Ranjan, J. “Business justification with business intelligence.” The journal of information and knowledge management systems, vol. 38(4), pp. 461-475,2008

Little, R., & Gibson, M. “Perceived Influences on Implementing Data Warehousing.” IEEE Transactions on Software Engineering , vol.29(4), pp.290-296, 2003

Downloads

Published

2020-03-22

How to Cite

Chikati, R. . (2020). How Business Intelligence Can Influence the Delivery of Excellence in Botswana Accountancy College (BAC). International Journal of Sciences: Basic and Applied Research (IJSBAR), 50(2), 75–86. Retrieved from https://gssrr.org/index.php/JournalOfBasicAndApplied/article/view/10996

Issue

Section

Articles