BatchDeduplicator 4.2

BatchDeduplicator is a program for regular doublet searches performed in address tables on a fixed schedule, in order to ensure the long-term quality of this data. Particularly repetitive advertising in the case of direct marketing and the unnecessary repeated maintenance of client and other address data can thus be avoided. Of course, this leads to a direct savings of costs. Furthermore, a doublet search between two tables can also take a list of customers who do not wish to receive marketing transmissions into consideration, which can save a lot of trouble.

Here is a brief overview of the features of BatchDeduplicator:

- Fast, largely automated and thus easy to use comparison of address databases for double addresses. The postal address (error-tolerant matching), telephone number, email address, address or customer number and tax number can all serve as matching criteria.
- Option to compare with blacklists and the enhancement of an address database using the comparison results with data from a second address database.
- Option to combine multiple tables into a single matching operation.
- User-defined universal matching, that can be used for any form of data.
- Numerous options for the further processing of the matching results: beside the direct deletion in the source file, it is also possible to flag the results in the source file, or to process further using a stored procedure, a duplicate-, results- or archive-file
- A deletion and results log that includes comments and your own logo, that can be saved as a PDF file, among others.
- The possibility of planning projects. For example, the program could be instructed to execute a certain project every Monday at 8 pm.
- The possibility of executing one or several projects by starting the program with command line parameters. An example of this would be: 'BatchDeduplicator -exec 1+5+7'
- Of course, all projects can also be started manually.

And much more ...

Release Info:	Major Update on Jan 05, 2015
Related Tags:	deduplication dedupe list cleaning data quality