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http://dx.doi.org/10.7236/JIIBC.2018.18.1.119

A Study on Reducing Data Obesity through Optimized Data Modeling in Research Support Database  

Kim, Hee-Wan (Division of Computer-Mechatronics, Shamyook University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.18, no.1, 2018 , pp. 119-127 More about this Journal
Abstract
The formal data used in the business is managed in a table form without normalization due to lack of understanding and application of data modeling. If the balance of the database design is destroyed, it affects the speed of response to the data query, and the data obesity becomes high. In this paper, it is investigated how data obesity improved through database design through optimized data modeling. The data query path was clearly visualized by square design through data modeling based on the relationship between object (data) and object, from the radial and task - oriented isolation design where data obesity is excessive. In terms of data obesity, the obesity degree of the current research support database was 57.2%, but it was 16.2% in the new research support database, and the data obesity degree was reducd by 40.5%. In addition, by minimizing redundancy of data, the database has been improved to ensure the accuracy and integrity of the data.
Keywords
Data Modeling; Data Obesity; Database Design; Data Query; Square Design;
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Times Cited By KSCI : 2  (Citation Analysis)
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