You might have had to seek common references between two data tables without these references beging always the same: misspelled names, addresses, descriptions, codes or identifiers different from one organization to the other…

Now docBird CrossReferencer allows you to automatically find similar references between two data tables. This tool is ideal for analyzing large volumes of data and for analyzing information that you frequently use: customer records, product catalogs, lists of bills, classification tables, etc … Tasks that seemed binding and even impossible before, will now be handled in a few clicks with docBird CrossReferencer.

docBird CrossReferencer determines matches according to your own rules of recognition. It compares the columns you specify (addresses or descriptions for example) using one of the many likeness algorithms the tool features. So you can configure your search rules according to the type of data to analyze.

Once your recognition rules specified, simply click a button to start the search. docBird CrossReferencer then displays a summary report of results listing the directly found references, the unknown ones and finally those for which the operating tool ‘was not sure’. For those, it allows you to manually select the right reference among the list of the most similar ones. At any time you have the opportunity to save the results of your search and to export them as lookup tables in the desired format.

docBird CrossReferencer supports multiple input formats (plain text, CSV, Excel …). With an intuitive interface, the tool is also easy to use. It also allows you to keep your work (your settings and your search results) in projects.