Abstract
Data cleaning is an automated process of detecting, removing and correcting incomplete, incorrect, inaccurate and irrelevant data from a record set. Our system works on simple text (*.txt) files using Extract, Transform and Load (ETL) model. In this paper we present a set of algorithms to correct errors such as alpha- numeric errors, invalid gender, invalid ID pattern and redundant ID error. The text files are used as data storage which stores data in a tabular format and the algorithms are applied on each field value depending on its nature.
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