Like manufacturing scrap and rework, data cleansing is merely rework to correct defects that would not be there if the processes worked properly. To be sure data cleansing is required for any data warehouse or conversion project to succeed. If data in a data warehouse is nonquality, the warehouse will fail. Data cleansing and correction are, simply put, part of the costs of nonquality data. Every hour consumed and dollar spent correcting data is an hour or dollar that cannot be spent doing something that adds value.
Information quality is quality data produced at the source.
Information quality improvement databases are designed properly and the processes are defined and operating properly. Information quality improves processes to prevent defective data from being created. Data cleansing attacks the symptoms of a problem. It fixes the results of faulty processes. Information quality attacks the root causes of data defects and eliminates the causes of nonquality information.