Yönetim Bilişim Sistemi Tasarımı Aşamasında İlişkisel Veri Modellemenin Önemi ve Kalitesi: İki Veri Modelinin Değerlendirmesi

Öz

Günümüzde insan, özel hayatında veya iş hayatında birçok işlemi bilgi sistemleri ile yapmaktadır. Bu işlemleri yaparken bilgi sistemlerinin ekranları vasıtası ile bilgi girişinde bulunur ve sonuçta bir çıktı elde eder. Bu girdilerin ve çıktıların bilgi sitemlerinde tutulduğu yer veri tabanlarıdır. Bilgi sistemlerinin temeli veri tabanıdır. İyi bir veri tabanının da temeli veri tabanı modelinin iyi bir şekilde yapılmasıdır. Dolayısı ile veri tabanının doğru bir şekilde kurulması hem kullanıcılar hem de sistem geliştiriciler açısından önemlidir. Bu çalışmanın amacı hem uygulayıcılar hem de araştırmacılara veri modeli oluşturulması aşamasında dikkat edilmesi gereken hususları göstermektir. Kapsamında ise ilişkisel veri tabanı modellemesi ile ilgili olarak yapılan çalışmalar, veri modelleme yöntem ve hususları ile uygulama kısmında veri modeli puan kartı ile iki projenin veri modeli incelenmiş, sonuçlar değerlendirilmiş ve veri modellemesi konusunda önerilerde bulunulmuştur. Sonuçta birinci model 83 puan ile iyi, ikinci model ise 68 puan ile orta üstü olgunluk seviyesinde yer almıştır.

Anahtar Kelimeler

• Veri modeli
• E-R modelleme
• İlişkisel veri tabanı
• Veri modeli kalitesi

Importance and Quality of Relational Data Modeling in Management Information System Design Phase: Evaluation of Two Data Models

Abstract

Today, people do many operations in their private or business life with information systems. While doing these operations, they enter information through the screens of the information systems and ultimately obtains an output. The databases are where these inputs and outputs are kept in information systems. The basis of information systems is the database. The basis of a good database is to make a good database model. Therefore, the correct establishment of the database is important for both users and system developers. The aim of this study is to show both practitioners and researchers the points that need to be taken into consideration during the creation of a data model. Within the scope of the studies about relational database modeling, data modeling methods and issues, and the data model scorecard in the application part, the data model of two projects were examined, the results were evaluated and recommendations were made on data modeling. As a result, the first model was good with 83 points, and the second model was at the upper-intermediate maturity level with 68 points.

Keywords

• Data model
• E-R modeling
• Relational database
• Data model quality

Kaynakça

1. Batini, C., Ceri, S., & Navathe, S. B. (1992). Conceptual Database Design An Entity-Relationship Approach. The Benjamin/Cummings Publishing.
2. Business Analysis Body of Knowledge (BABoK) A Guide to Business Analysis Body of Knowledge. (2015). International Institute of Business Analysis.
3. Chen, P. P. S. (1976). The Entity-Relationship Model-Toward a Unified View of Data. ACM Transactions on Database Systems, 1(1), 9-36.
4. Chmura, A., & Heumann, J. M. (2005). Logical Data Modeling What It Is and How To Do It. Springer.
5. Codd, E. F. (1970). A Relational Model of Data For Large Shared Data Banks. Communications of the ACM, 13(6), 377-387.
6. Codd, E. F. (1979). Extending the Database Relational Model to Capture More Meaning. ACM Transactions on Database Systems, 4(4), 397-434.
7. Codd, E. F. (1982). Relational Database: A Practical Foundation for Productivity. Communications of the ACM, 25(2), 109-117.
8. Dama-Dmbok-Data Management Body Of Knowledge (Second Edition). (2017). Technics Publications.

9. Date, C. J. (2019). Database Design and Relational Theory Normal Forms and All That Jazz (Second Edition). Apress.
10. Dubielewicz, I., Hnatkowska, B., Huzar, Z., & Tuzinkiewicz, L. (2007). Evaluation of MDA/PSM Database Model Quality in the Context of Selected Non-Functional Requirements. 2nd International Conference on Dependability of Computer Systems(DepCoS-RELCOMEX'07).
11. Fenerci, T. (2001). Veri Tabanı Tasarımının Önemi ve Normalizasyon Süreci. Türk Kütüphaneciliği, 15, 123-135.
12. Genero, M., & Piattini, M. (2002). Quality in Conceptual Modelling. M. G. Piattini, C. Calero, & M. Genero, Information And Database Quality. Springer Science and Business Media.
13. Getta, J. R. (2018). Automated Evaluation of Correctness and Quality of Database Conceptual Schemas. BDET 2018: Proceedings of the 2018 International Conference on Big Data Engineering and Technolog, (s. 20-25).
14. Halpin, T., & Morgan, T. (2008). Information Modeling and Relational Databases (First Edition). Elsevier.
15. Harrington, J. L. (2016). Relational Database Design and Implementation (Fourth Edition). Elsevier.
16. Hoberman, S. (2015). Data Model Scorecard Applying the Industry Standard on Data Model Quality (First Edition). Technics Publications.
17. Kesh, S. (1995). Evaluating the Quality of Entity Relationship Models. Information and Sojlware Technology, 37(12), 681-689.
18. Laudon, K. C., & Laudon, J. P. (2018). Management Information Systems Managing the Digital Firm (Fifteenth Global Edition Edition). Pearson.
19. Moody, D. L. (1994). What Makes a Good Data Model? Evaluating Quality of Entity Relationship Models-Business Modelling and Re-Engineering 13th International Conference on the Entity-Relationship Approach. United Kingdom,: Springer-Verlag.
20. Moody, D. L. (1996). B. Thalheim (Dü.), Graphical Entity Relationship Models: Towards a More User Understandable Representation of Data - Conceptual Modeling ER'96, 15th International Conference on Conceptual Modeling Cottbus. Germany, Springer.
21. Moody, D. L. (1998). Tok Wang, Ling Sudha Ram , & Mong Li Lee (Dü.), Metrics for Evaluating the Quality of Entity Relationship Models-Conceptual Modeling - ER ’98, 17th International Conference on Conceptual Modeling. Springer.
22. Moody, D. L., & Shanks, G. G. (2003). Improving the Quality of Data Models: Empirical Validation of a Quality Management Framework. Information Systems, 28, 619-650.
23. O’Driscoll, K. (2016). The Agile Data Modelling & Design Thinking Approach to Information System Requirements Analysis. Journal of Decision Systems, 25(1), 632-638.
24. Redman, T. (2001). Data Quality: The Field Guide. Digital Press.
25. Silberschatz, A., Korth, H. F., & Sudarshan, S. (2020). Database System Concepts (Seventh Edition). McGraw-Hill Education.
26. Thalheim, B. (2000). Entity- Relationship Modeling - Foundations of Database Technology. Springer.
27. Uzun, E., Buluş, H. N., & Erdoğan, C. (2018). Veritabanı Tasarımının Yazılım Performansına Etkisi: Normalizasyona karşı Denormalizasyon. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 28(2), 887-895.