Remadder is an affordable and powerful record linkage software, with great fuzzy record matching and data deduplication capabilities. It is a tool for records linkage analysis, which can be used both to identify related records in two separate data sets or to identify duplicate records in a data set. 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. Due to its inherent complexity, fuzzy match analysis is a popular subject of scientific research and academic papers. Some of the researchers even tend to build their own software, but those programs suffer from their complexity and it is really necessary to understand all the advanced mathematics and algorithms in order to be able to use it. This is not something that can be expected from an average user facing data linkage problem and wanting to be able to solve it in matter of hours. On the other hand, there are huge corporate entity resolution framework solutions produced by big software companies oriented toward huge corporate customers. These solutions are complex and affordable only to big companies and corporate users. Remadder places itself in the middle and provides powerful fuzzy match records linkage solution for mere mortals and regular office users. 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. 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 its intuitive graphical user interface and low pricing, Remadder provides superb solution for fuzzy match records linkage for any business case.
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