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An Enhanced Common Data Cleaning Framework for Data mining


Agusthiyar. R, Dr. K. Narashiman
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In this information era, there is a huge availability of data but the information is not enough to meet the requirements. This creates an urgent need for data cleaning and data cleaning solutions become highly important for data mining users. Normally, data cleaning deals with detecting, eliminating errors and inconsistencies in large data sets. For any real world data set, doing this task manually is very cumbersome as it involves huge amount of human resource and time. This means several organizations spend millions of dollars per year to detect data errors. Due to this wide range of possible data inconsistencies and the sheer data volume, data cleaning is considered to be one of the biggest problems in data warehousing. Normally the data cleaning is required when multiple data sources need to be integrated. In this research work an Enhanced Common Data Cleaning (ECDC) framework has been developed and proposed.

Agusthiyar. R, Dr. K. Narashiman

Data cleaning, Data mining, Extract, Transform and Load (ETL), Extensible Markup Language (XML), Enhanced Common Data Cleaning (ECDC)

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Publication Details

Published in : Volume 2 | Issue 5 | September-October - 2016
Date of Publication Print ISSN Online ISSN
2016-10-31 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
438-444 IJSRSET1625110   Technoscience Academy

Cite This Article

Agusthiyar. R, Dr. K. Narashiman , "An Enhanced Common Data Cleaning Framework for Data mining", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 5, pp.438-444, September-October-2016.
URL : http://ijsrset.com/IJSRSET1625110.php