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Data Cleansing

Data Cleansing

Finally it would document the results of the previous steps on metadata. This helps the following cleanups are better able to recognize and address end-users of applications can perform better the operations of a DW. As you can see, it is rather tedious to carry this process manually, and to do automated application would require sophisticated algorithms containing grammatical analysis (parsing) of addresses, macheo algorithms and huge tables with lots of entries that provide synonyms for different parts of the addresses. In some cases it is possible to create effective cleaning programs. But in the case of large databases, imprecise and inconsistent use of commercial tools already exist, can be almost mandatory. WHAT IS STANDARDIZATION? Importance of standardization ADDRESS FOR COMPANIES TODAY Standardization is one of the six steps necessary to carry out data cleansing.

This is to separate information in different fields as well as change some criteria for better handling and manipulation of data. Having standardized data, consistent quality, it is very useful and sometimes vital for businesses that use data warehouses. An example of this are those organizations whose data on their customers are of great value. The management of names and addresses of customers is no easy task. Over 50% of Internet companies can not respond to the needs of all customers and can not relate to them because of the lack of quality data. 2 To communicate effectively with their customers, by phone, mail or in any other way, a company must maintain a list of their customers extremely clean.