Academic Business Intelligence: Can a Small and Medium-sized University Afford to Build and Deploy it within Limited Resources?

Wahyudi Agustiono

= http://dx.doi.org/10.20473/jisebi.5.1.1-12
Abstract views = 329 times | views = 339 times

Abstract


Background: For many years, researches on Business Intelligence (BI) development have been popular in primary industry (trading, telecommunication, and manufacturing). Nevertheless, the academic sector has not been the primary beneficiary. This lack of practices also means there has been limited knowledge relating to the development of BI in the academic sector

Objective: This study presents the development of an Academic Business Intelligence (ABI). Taking an actual ABI development project in a small and medium-sized university in Indonesia context, it specifically sought to understand as to why the university needed an ABI and how it could be developed within the limited resources (funding, IT infrastructure and expertise).

Methods: Following the business intelligence development roadmap, this study was able to develop an ABI as an attempt to provide a smart way for generating valuable information from scattered data interactively. It also successfully deployed the newly developed ABI into the existing IT legacy and then run a series of pilot testing involving the intended users.

Results: The results showed the acceptance rate was high (87.25%) and suggested that the system found to be usable for conducting students' performance assessment and decision making faster. In short, this study contributes to the growing body of BI development literature by providing empirical evidence on how to successfully develop a BI within the unique context of the academic sector.

Conclusion: Considering the findings, this study also draws practical recommendations and highlights a few limitations from which future study could address, especially when developing BI or similar ABI in particular.


Keywords


Business Intelligence; Academic Business Intelligence; Business Intelligence Development; BI Development Roadmap; Higher Education;Academic Performance Appraisal

Full Text:

PDF

References


Gartner. Gartner IT-glossary: Gartner Inc; 2017 [cited 17 24 January 2018]. Available from: https://www.gartner.com/it-glossary/business-intelligence-bi/.

Marjamäki P. Evolution and Trends of Business Intelligence Systems: A Systematic Mapping Study. Oulu, Finland: University of Oulu; 2017.

BI-Survey. Importance of Big Data Security Analytics in Different Industries 2018. Available from: https://bi-survey.com/big-data-security-analytics-importance-industries.

Kollwitz C, Dinter B, Krawatzeck R. Tools for Academic Business Intelligence and Analytics Teaching: Results of an Evaluation. Analytics and Data Science: Springer; 2018. p. 227-50.

Luhn HP. A business intelligence system. IBM Journal of research and development. 1958;2(4):314-9.

Codd EF. A relational model of data for large shared data banks. Communications of the ACM. 1970;13(6):377-87.

Gilad B, Gilad T. The business intelligence system: a new tool for competitive advantage: American Management Association; 1988.

Gbosbal S, Kim SK. Building effective intelligence systems for competitive advantage. Sloan Management Review (1986-1998). 1986;28(1):49.

Cody WF, Kreulen JT, Krishna V, Spangler WS. The integration of business intelligence and knowledge management. IBM systems journal. 2002;41(4):697-713.

Wang H, Wang S. A knowledge management approach to data mining process for business intelligence. Industrial Management & Data Systems. 2008;108(5):622-34.

Sahay B, Ranjan J. Real time business intelligence in supply chain analytics. Information Management & Computer Security. 2008;16(1):28-48.

Chung W, Chen H, Nunamaker Jr JF. A visual framework for knowledge discovery on the Web: An empirical study of business intelligence exploration. Journal of Management Information Systems. 2005;21(4):57-84.

Marshall B, McDonald D, Chen H, Chung W. EBizPort: collecting and analyzing business intelligence information. Journal of the American Society for information Science and Technology. 2004;55(10):873-91.

Sun Z, Zou H, Strang K, editors. Big data analytics as a service for business intelligence. Conference on e-Business, e-Services and e-Society; 2015: Springer.

Hang Y, Fong S, editors. Real-time business intelligence system architecture with stream mining. Digital Information Management (ICDIM), 2010 Fifth International Conference on; 2010: IEEE.

Kirchner K, Herzberg N, Rogge-Solti A, Weske M. Embedding conformance checking in a process intelligence system in hospital environments. Process Support and Knowledge Representation in Health Care: Springer; 2013. p. 126-39.

Davenport TH, Dyché J. Big data in big companies. International Institute for Analytics. 2013;3.

Hodinka M, Štencl M, Hřebíček J, Trenz O. Business Intelligence in Environmental Reporting Powered by XBRL. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. 2014;62(2):355-62.

Hill J, Scott T. A consideration of the roles of business intelligence and e-business in management and marketing decision making in knowledge-based and high-tech start-ups. Qualitative Market Research: An International Journal. 2004;7(1):48-57.

Wirtschaft P, Schieder C, Kurze C, Gluchowski P, Bohringer M. Benefits and challenges of business intelligence adoption in small and medium-sized enterprises. 18th European Conference on Information Systems; 6-9 June; Pretoria, South Africa2010.

Wixom B, Ariyachandra T, Douglas DE, Goul M, Gupta B, Iyer LS, et al. The current state of business intelligence in academia: The arrival of big data. CAIS. 2014;34:1.

Wang Y. Business intelligence and analytics education: hermeneutic literature review and future directions in IS Education. 2015.

Guster D, Brown CG. The application of business intelligence to higher education: Technical and managerial perspectives. Journal of Information Technology Management. 2012;23(2):42-62.

Marjanovic O, editor Sharing and reuse of innovative teaching practices in emerging business analytics discipline. System Sciences (HICSS), 2013 46th Hawaii International Conference on; 2013: IEEE.

Pantazos K, Vatrapu R, editors. Enhancing the Professional Vision of Teachers: A Physiological Study of Teaching Analytics Dashboards of Students' Repertory Grid Exercises in Business Education. System Sciences (HICSS), 2016 49th Hawaii International Conference on; 2016: IEEE.

Di Valentin C, Emrich A, Werth D, Loos P. Assistance System for Personalized Learning in Vocational Education. 2014.

Presthus W, Bygstad B. Business intelligence in college: a teaching case with real life puzzles. J Inform Technol Educ: Innovations In Practice. 2012;11.

Chen H, Chiang RH, Storey VC. Business intelligence and analytics: From big data to big impact. MIS quarterly. 2012;36(4).

Dell’Aquila C, Di Tria F, Lefons E, Tangorra F. Business intelligence applications for university decision makers. WSEAS Transactions on Computers. 2008;7(7):1010-9.

Ta’a A, Bakar MA, Saleh AR, editors. Academic business intelligence system development using SAS® tools. Online Proc of the SAS Global Forum; 2008.

Moturi CA, Emurugat A. Prototyping an academic data warehouse: case for a Public University in Kenya. British Journal of Applied Science & Technology. 2015;8(6):550-7.

Di TF, Lefons E, Tangorra F. Academic data warehouse design using a hybrid methodology. Computer Science and Information Systems. 2015;12(1):135-60.

Apraxine D, Stylianou E, editors. Business intelligence in a higher educational institution: The case of University of Nicosia. 2017 IEEE Global Engineering Education Conference (EDUCON); 2017 25-28 April 2017.

Zucca J. Business intelligence infrastructure for academic libraries. Evidence Based Library and Information Practice. 2013;8(2):172-82.

Laitinen M, Saarti J. A model for a library-management toolbox: Data warehousing as a tool for filtering and analyzing statistical information from multiple sources. Library management. 2012;33(4/5):253-60.

Petrovic S, Stefanovic D, Lolic T, Mirkovic M. Development of Business Intelligence systems to predict Behaviour Patterns of Students. XVII International Scientific Conference on Industrial Systems (IS'17)2017.

Kleesuwan S, Mitatha S, Yupapin PP, Piyatamrong B. Business intelligence in Thailand's higher educational resources management. Procedia-Social and Behavioral Sciences. 2010;2(1):84-7.

Hasan NA, Miskon S, Ahmad N, Ali NM, Hashim H, Syed N, et al. Business intelligence readiness factors for higher education institution. Journal of Theoretical and Applied Information Technology. 2016;89(1):174.

Record Persson J, Sjöö E. Business Intelligence–its impact on the decision-making process at higher education institutions: A case study at Karlstad University. 2017.

Lee MT, Widener SK. The performance effects of using business intelligence systems for exploitation and exploration learning. Journal of Information Systems. 2015;30(3):1-31.

Musa S, Ali NBM, Miskon SB, Giro MA, editors. Success Factors for Business Intelligence Systems Implementation in Higher Education Institutions–A Review. International Conference of Reliable Information and Communication Technology; 2018: Springer.

Zulkefli NA, Miskon S, Hashim H, Alias RA, Abdullah NS, Ahmad N, et al. A business intelligence framework for higher education institutions. Journal of Theoretical and Applied Information Technology 2016;89(1):174-81.

Muntean M, Bologa A-R, Bologa R, Florea A. Business intelligence systems in support of university strategy. Recent Researches in Educational Technologies. 2011:118-23.

Di Tria F, Lefons E, Tangorra F. Academic data warehouse design using a hybrid methodology. Computer Science & Information Systems. 2015;12(1).

Moss LT, Atre S. Business intelligence roadmap: the complete project lifecycle for decision-support applications: Addison-Wesley Professional; 2003.

Agustiono W, Nasrullah WA. Desain academic business intelligence untuk akreditasi: Studi kasus Universitas Trunojoyo. 2017.

McConnell S. Rapid development: taming wild software schedules: Pearson Education; 1996.

Lewis JR. IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. International Journal of Human‐Computer Interaction. 1995;7(1):57-78.

Baepler P, Murdoch CJ. Academic analytics and data mining in higher education. International Journal for the Scholarship of Teaching and Learning. 2010;4(2):17.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Authors

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN 2443-2555 (online) 2598-6333 (print). Published by Universitas Airlangga.
 All article published in JISEBI are open access and under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

JISEBI Stats