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Asian Journal of Information Technology
Year: 2017  |  Volume: 16  |  Issue: 9  |  Page No.: 699 - 705

Analyzing and Improving the Performance of Decision Database with Enhanced Momentous Data Types

M. Muthukumar, P. Senthil Pandian and K. Karthikeyan    

Abstract: In the current digital age, volume of data is getting increased by 59% on every year worldwide. According to research, it is estimated that 70-85% of data is unstructured and more than 20% performance degradation happens due to improper database design. There are many factors which may influence the performance of the database among the factors a data type plays an important role. Choosing the right data type for each column is most essential in either heavy transaction or less transaction tables. Proper database design provides multiple benefits like minimized disk usage, less consumptions of CPU and resources and improved query performance. The proper usage of data types in the database improves the performance of the whole system. These data types are of different types and should be used in an intelligent way to achieve the expected behavior. This study demonstrates how to choose the correct data types to design efficient database and also identifies which data type should be used or not to be used.

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