Developing a Cooperative Data Cleaning Tool

Abstract

Abstract Presently, large amount of data generated by organizations drives their business decisions. The data is usually inconsistent, inaccurate and incomplete. Poor data quality may lead to incorrect decisions for the organizations and hence, negatively affect them. Thus, high quality data is of utmost priority to draw good and valid business decisions and strategies. Data cleaning is the ultimate way to solve the data quality issues. But, data cleaning is really a time consuming task. Thus, tools which can help with the task are needed. This demands data cleaning tools for systematically examining data for errors and automatically cleaning them using algorithms. These data cleaning tools helps organizations save time and increase their efficiency. In this thesis, we develop a cooperative, free and open source data cleaning standalone application ‘DataCleaningTool’ in order to achieve the task of data cleaning. This tool is able to identify the potential data problems and report results such that the users can take informed decisions to clean data effectively.