Date of Award
1-20-2025
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Education
First Advisor
Meng-Jia Wu
Abstract
The database system is essential to modern life and helps us in our day-to-day existence, even though it is invisible to us. The most optimal way to architect a new but efficient database is a modeling technique called conceptual data modeling. Despite this importance, research studies have suggested a divergence between actual practice and the ideal expectation from practitioners. Therefore, it was imperative to establish the ground truth in this context and explore the reasons behind the gap between practice and expectation. This mixed-method study used a survey and interviews to establish that only a small fraction of practitioners consistently use conceptual data modeling. Contrary to previous research, factors such as education, location, size of the industry, and experience of the practitioners were found to have negligible impact on the usage of conceptual data modeling. However, irrespective of these factors, even one course of database design or modeling at any level can have a significant positive impact on practitioners’ inclination toward the usage of conceptual data modeling. Also, a diverse set of experiences across multiple projects makes practitioners realize the importance of conceptual data modeling. It is also established that a lack of conceptual data modeling often leads to waste and expensive failure. This research study has profound implications for (a) the academic programs that teach database systems and (b) the corporate training programs that educate novice data modelers about best practices. As a recommendation, academic programs in database systems must put more emphasis and time on conceptual data modeling and not restrict themselves to technical implementation topics alone. Similarly, corporate training programs must xi realize that conceptual data modeling is essential for the project's success and to reduce waste or failure. Hence, conceptual data modeling must be essential to corporate training programs for data modelers. Also, conceptual data modeling will remain highly relevant with changing paradigms like AGILE, and the arrival of innovative technologies like AI will make it an even more important part of a successful project.
Recommended Citation
Sharma, Abhishek, "Examining the Current Utilization of Conceptual Data Modeling in Database Modeling Practices: Mixed Methods Research" (2025). Dissertations. 4151.
https://ecommons.luc.edu/luc_diss/4151
