Removing Inconsistencies and Errors From Original Data Sets Through Data Cleansing
The problem of data cleaning, which consists of removing inconsistencies and errors from original data sets, is well known in the area of decision support systems and data warehouses. This holds regardless of the application - relational database joining, web-related, or scientific. In all cases, existing ETL (Extraction Transformation Loading) and data cleaning tools for writing data cleaning programs are insufficient. There were so many limitations in the management system like data inconsistency, inconvenience in retrieval of data etc. Because of all these limitations the authors have to face the problems like memory inefficiency and heavy in consumption of time and also lack of quality.