Abstract
Data quality (DQ) is as old as the data is. In last few years it is found that DQ can’t be ignored during the process of data warehouse (DW) construction and utilization as it is the major and critical issue for knowledge experts, workers and decision makers who test and query the data for organizational trust and customer satisfaction. Low data quality will lead to high costs, loss in the supply chain and degrade customer relationship management. Hence to ensure the quality before using the data in DW, CRM (Customer Relationship Management), ERP (Enterprise Resource Planning)or business analytics application, it needs to be analyzed and cleansed. In this, we are going to find out the problem regarding dirty data and try to solve them.
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