earticle

영어

Increasing number of data is occurs because of high demand from organizations to run their daily business operations. Most of organizations have an information system in order to provide quality information to the organizations. In order to provide the quality information, the information system must be able to filter any dirty from data sources. One of the type dirty data is inconsistent data. Inconsistent data is occurs because of data structured from different data sources are different. Four latest techniques to detect and reduce inconsistent data have been identified. These techniques are rough set, logic analysis of inconsistent data, fuzzy multi attributes decision making and functional dependencies of corresponding relation variable. In this paper, these techniques have been studied described with suitable examples. The purpose of studied is to identify advantages, disadvantages and any potential enhancement in reducing inconsistent data from database.