Data cleaning based on similarities involves identification of “close” tuples, where closeness is evaluated using a variety of similarity functions chosen to suit the domain and application. Current approaches for efficiently implementing such similarity joins are tightly tied to the chosen similarity function. In this paper, we compare between two cleaning tools. The two cleaning tools considered are Microsoft SQL Server2012 Data Quality Services and Winpure clean and match software.
Data Quality Services is a knowledge-based system that performs both computer-assisted and interactive cleansing and matching processes using the created knowledge base.
WinPure Clean & Match 2009 is the latest edition, following on from the award-winning Clean & Match 2007. It builds upon its data duplication module and now features advanced fuzzy matching logic to identify and remove more duplications.
The comparison between the above two tools is carried out using academic datasets, with the Weather dataset as its input.
Dr.Abdelrahman Elsharif Karrar : Taibah University
Saudi Arabia.
Moez Mutasim Ali : University of Science and Technology
Sudan.
Data Cleaning, Data Cleansing, Data Quality Services, Winpure, Datasets
Data Quality Services Provide several steps to begin the cleaning process, in the other way WinPure Clean and Match 2013 Software provide easy
Data Quality Services Provide options for an automated process to clean the source data or manually go over the cleansing results and fix issues that are found, in the other way WinPure Clean and Match 2013 Software don’t provide the manual option.
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