International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Designing a Data Warehouse for Multidimensional Modelling in Higher Education Institutions

Abstract

The development of a data warehouse has become essential as real-life problems nowadays deal with multidimensional data, and data warehouses provide a trustworthy foundation for decision-making in this situation. This paper presents the development stages of a data warehouse for managing the admission process in higher education institutions. Fact and dimension tables are arranged using the snowflake schema for the logical arrangement of the multidimensional database. The paper also presents a multidimensional model to perform multidimensional analysis on admission data. The admission data warehouse and the multidimensional cubes are implemented in PostgreSQL. The developed system will provide the university administrators with various analytical reports that can enhance personalized and transparent experience for students.

Country : India

1 Vijay Dev2 Rajesh Sharma3 Preetvanti Singh

  1. Research Scholar, Department of Physics & Computer Science, Dayalbagh Education Institute, Agra, India
  2. Research Scholar, Department of Physics & Computer Science, Dayalbagh Education Institute, Agra, India
  3. Professor, Department of Physics & Computer Science, Dayalbagh Education Institute, Agra, India

IRJIET, Volume 9, Issue 5, May 2025 pp. 145-158

doi.org/10.47001/IRJIET/2025.905019

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References

  1. T. Park and H. Kim, “A data warehouse-based decision support system for sewer infrastructure management,” Autom. Constr., vol. 30, pp. 37–49, 2013.
  2. K. Jo et al., “Long-term prediction models for vision-threatening diabetic retinopathy using medical features from data warehouse,” Sci. Rep., vol. 12, no. 1, p. 8476, 2022.
  3. M. Kaspar et al., “Querying a Clinical Data Warehouse for Combinations of Clinical and Imaging Data,” J. Digit. Imaging, vol. 36, no. 2, pp. 715–724, 2023.
  4. L. Liu, “Visualized Analysis of Tourism Big Data based on Real-Time Analysis and Complexity Measurement,” in 2021 6th International Conference on Inventive Computation Technologies (ICICT), IEEE, 2021, pp. 497–500.
  5. P. Singh and V. Dev, “Data Warehouse with OLAP Technology for the Tourism Industry,” in Encyclopedia of Data Science and Machine Learning, IGI Global, 2023, pp. 191–211.
  6. A.K. Hamoud, K. H. Marwah, Z. Alhilfi, and R. H. Sabr, “Implementing data-driven decision support system based on independent educational data mart,” Int. J. Electr. Comput. Eng., vol. 11, no. 6, 2021.
  7. S. Zhang and L. You, “Research on higher education intelligent decision system based on data mining,” in 2021 4th International Conference on Information Systems and Computer Aided Education, 2021, pp. 2863–2871.
  8. C. U. Serasinghe, D. C. R. Jayakody, K. T. M. N. Dayananda, and D. Asanka, “Design and Implementation of Data Warehouse for a Higher Educational Institute in Sri Lanka,” in 2021 6th International Conference for Convergence in Technology (I2CT), IEEE, 2021, pp. 1–5.
  9. X. Yu, “The Application of Data Warehouse in Teaching Management in Colleges and Universities,” in Journal of Physics: Conference Series, vol. 1738, IOP Publishing, 2021.
  10. A.Bahaaudeen, “The Impact of the Data Warehouse on Decision Making Quality and Speed in Higher Education,” in 2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD), IEEE, 2023, pp. 1–10.
  11. J. Chen, J. Zhan, and F. Tian, “Research on the Construction of a Data Warehouse Model for College Student Performance,” in International Conference of Pioneering Computer Scientists, Engineers and Educators, Singapore; Singapore: Springer Nature, 2023, pp. 408–419.
  12. M. S. Farhan, A. Youssef, and L. Abdelhamid, “A Model for Enhancing Unstructured Big Data Warehouse Execution Time,” Big Data Cogn. Comput., vol. 8, no. 2, 2024.
  13. R. Kimball and M. Ross, The data warehouse toolkit: The definitive guide to dimensional modeling. John Wiley & Sons, 2013.

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