Academic Data Warehouse Modeling in Higher Education Using Nine-Step Design Methodology
DOI:
https://doi.org/10.51519/journalisi.v4i4.399Keywords:
Data Warehouse, Star Schema, Nine Step MethodologyAbstract
Data and information are essential in various fields today, as well as in the field of education, especially in universities. Some universities already have information systems that support data and information needs. However, the system has not been integrated, so it cannot provide data and information needs quickly and in an integrated manner. Information systems in universities are still primarily departmental because each was built at a different time and uses another platform. The departmental nature of this information system causes inaccuracies and inconsistencies of data that drive the information produced in reports and data reused in transactions to be invalid. Invalid data, in the end, also impacts decision-making taken by management. This study aims to develop a data warehouse at a university to integrate academic data using a star schema. The method used is the Nine Step Methodology. The result of this research is data warehouse architecture used in the academic field; fact tables and ERDs have been designed at the current stage of designing a Prototype of the Study Program Performance Sheet (LKPS).
Downloads
References
L. W. Santoso and Yulia, “Data Warehouse with Big Data Technology for Higher Education,” in Procedia Computer Science, 2017, vol. 124, pp. 93–99. doi: 10.1016/j.procs.2017.12.134.
S. Bouaziz, A. Nabli, and F. Gargouri, “Design a data warehouse schema from document-oriented database,” Procedia Comput Sci, vol. 159, pp. 221–230, 2019, doi: 10.1016/j.procs.2019.09.177.
M. Mirzaei, N. Zaerpour, and R. de Koster, “The impact of integrated cluster-based storage allocation on parts-to-picker warehouse performance,” Transp Res E Logist Transp Rev, vol. 146, Feb. 2021, doi: 10.1016/j.tre.2020.102207.
M. AlMeghari, S. Taha, H. Elmahdy, and X. Shen, “A proposed authentication and group-key distribution model for data warehouse signature, DWS framework,” Egyptian Informatics Journal, no. xxxx, 2020, doi: 10.1016/j.eij.2020.09.002.
A. Filiana, A. G. Prabawati, M. N. A. Rini, G. Virginia, and B. Susanto, “Perancangan Data Warehouse Perguruan Tinggi untuk Kinerja Penelitian dan Pengabdian kepada Masyarakat,” Jurnal Teknik Informatika dan Sistem Informasi, vol. 6, no. 2, pp. 174–183, 2020, doi: 10.28932/jutisi.v6i2.2557.
M. Souibgui, F. Atigui, S. Zammali, S. Cherfi, and S. ben Yahia, “Data quality in ETL process: A preliminary study,” Procedia Comput Sci, vol. 159, pp. 676–687, 2019, doi: 10.1016/j.procs.2019.09.223.
V. Khatibi, A. Keramati, and F. Shirazi, “Deployment of a business intelligence model to evaluate Iranian national higher education,” Social Sciences & Humanities Open, vol. 2, no. 1, p. 100056, 2020, doi: 10.1016/j.ssaho.2020.100056.
A. Cuzzocrea, “SpPolap: Computing privacy-preserving OLAP data cubes effectively and efficiently algorithms, complexity analysis and experimental evaluation,” Procedia Comput Sci, vol. 176, pp. 3831–3842, 2020, doi: 10.1016/j.procs.2020.09.337.
D. Nurmalasari, D. H. Qudsi, M. S. Zulvi, and W. Nengsih, “Pemodelan Data dengan Skema Galaksi pada Data Lulusan,” pp. 123–129, 2020.
O. A. Omitaomu et al., “A new methodological framework for hazard detection models in health information technology systems,” J Biomed Inform, vol. 124, Dec. 2021, doi: 10.1016/j.jbi.2021.103937.
R. Kimball, M. Ross, and A. A. Anisimov, The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (2nd Edition), vol. 32, no. 3. 2003. doi: 10.1145/945721.945741.
L. W. Santoso and Yulia, “Data Warehouse with Big Data Technology for Higher Education,” Procedia Comput Sci, vol. 124, pp. 93–99, 2017, doi: 10.1016/j.procs.2017.12.134.
R. Martins, M. T. Pereira, L. P. Ferreira, J. C. Sá, and F. J. G. Silva, “Warehouse operations logistics improvement in a cork stopper factory,” in Procedia Manufacturing, 2020, vol. 51, pp. 1723–1729. doi: 10.1016/j.promfg.2020.10.240.
S. W. Y. Cheng, K. L. Choy, and H. Y. Lam, “A workflow decision support system for achieving customer satisfaction in warehouses serving machinery industry,” in IFAC-PapersOnLine, May 2015, vol. 28, no. 3, pp. 1714–1719. doi: 10.1016/j.ifacol.2015.06.333.
R. K. Singh, N. Chaudhary, and N. Saxena, “Selection of warehouse location for a global supply chain: A case study,” IIMB Management Review, vol. 30, no. 4, pp. 343–356, Dec. 2018, doi: 10.1016/j.iimb.2018.08.009.
Downloads
Published
Issue
Section
License
Authors Declaration
- The Authors certify that they have read, understood, and agreed to the Journal of Information Systems and Informatics (JournalISI) submission guidelines, policies, and submission declaration. The submission has been prepared using the provided template.
- The Authors certify that all authors have approved the publication of this manuscript and that there is no conflict of interest.
- The Authors confirm that the manuscript is their original work, has not received prior publication, is not under consideration for publication elsewhere, and has not been previously published.
- The Authors confirm that all authors listed on the title page have contributed significantly to the work, have read the manuscript, attest to the validity and legitimacy of the data and its interpretation, and agree to its submission.
- The Authors confirm that the manuscript is not copied from or plagiarized from any other published work.
- The Authors declare that the manuscript will not be submitted for publication in any other journal or magazine until a decision is made by the journal editors.
- If the manuscript is finally accepted for publication, the Authors confirm that they will either proceed with publication immediately or withdraw the manuscript in accordance with the journal’s withdrawal policies.
- The Authors agree that, upon publication of the manuscript in this journal, they transfer copyright or assign exclusive rights to the publisher, including commercial rights














