ReMaDDer 1.0.
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ReMaDDer screenshot  |
Remadder is a software tool which can be used both to identify related records in two separate data sets or to identify duplicate records in a data set. This class of tasks is commonly reffered as record linkage, data matching, data duplicate detection, data deduplication, etc. Remadder especially successfully addresses hard problem of fuzzy data matching when two related data sets does not share exact common unique identifier. Instead of usual and simple primary/foreign key relational approach, in such cases data matching has to be established on basis of string fuzzy match similarity. This, however, is a complex and resource extensive task exhausting even for the most powerful computers of today. Remadder uses an inventive and pragmatic approach for fuzzy match analysis, by utilizing combination of two different string comparison similarity metrics: normalized Levenshtein distance and Trigram similarity. These can be combined in flexible way in order to provide best results. By allowing users to define exact matching constraints, fuzzy matching constraints and all other constraints in visual and intuitive way, all the complexity of the fuzzy match analysis is hidden from the user and he/she can focus on the business case, rather than technical issues. That is where Remadder software really shines and clearly distinguishes itself from competition. By its intuitive graphical user interface and low pricing, Remadder provides superb solution for fuzzy match records linkage for any business case.
Program Details
| Released: | 2016-03-18 |
| More: | All programs by this author |
| Downloads: | 158 |
| License Type: | Shareware |
| Platform: | WinXP,WinVista,WinVista x64,Win7 x32,Win7 x64,Win2000,WinOther,Windows2000,Windows2003,WinServer,Windows Vista Ultimate,Windows Vista Ultimate x64,Windows Tablet PC Edition 2005,Windows Media Center E |
| Homepage: | http://remaddersoft.wix.com/remadder |
| Price: | $10.00 US |
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ReMaDDer fuzzy match records linkage and data deduplication software |