Understanding Different Techniques Of Data Cleaning And Different Operations Involved
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Abstract
Identifying the problems related to inaccurate data and then correcting of detected errors addresses to data cleansing and provides an overview of the main solution and its scope. The improved quality of unreasonable data helps in data redundancy avoiding all sorts of omissions and increasing the consistency of data in data warehouse. The uncleansed data diminishes the importance of Data Mining and Data Warehousing. Since, data is a major asset in many companies and industries, the specifying of problem statement and solving it to enhance the identification of potential errors leads to better understanding of Data and Data Mining assets. The different methods of data cleansing are surveyed to provide a complete overview on benefits of data cleaning and various techniques involved in it. The main purpose of this article is to meet the growing demands of industry by providing the standardized data with the help of research on different algorithms available in the market which proves out to be beneficial in cleaning of data.
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