Contact us.
We will be happy to help you with your data quality issues.
TOLERANT Software
GmbH & Co. KG
Büchsenstr. 26
70174 Stuttgart, Germany
Phone: +49 711 400 4250
Fax number: +49 711 400 425 01
info@tolerant-software.de
www.tolerant-software.de
TOLERANT Match Pseudonymization
TOLERANT productsIf personal characteristics – e.g. name, address, telephone number – are replaced by pseudonyms, similar data records are no longer recognized with today’s standard methods, even in the case of minor deviations. TOLERANT Software provides a solution for fuzzy searches on fully pseudonymized data.
DQ tools in the Docker container
TOLERANT productsWhat if it could be even easier to use TOLERANT tools? For this, we pack your tools into practical containers that are located on a so-called Docker host. This host is – similar to a freight container ship – a large container that transports many containers.
Fuzzy exchange
TOLERANT productsThe products of Fuzzy! Informatik will no longer be supported in the future. Reference data – e.g. for Fuzzy! Post – will no longer be available. Therefore, it is necessary for all customers who have successfully used Fuzzy! products so far to think about a suitable replacement solution.
EU GDPR data protection query
TOLERANT productsThis enables them to respond to GDPR data protection requests easily and on time. Our TL Search solution creates a central search index and brings together the data from their various sources there, such as from the online store or CRM, ERP, Point of Sales systems.
TOLERANT Tools for data stewards
TOLERANT productsBecause TOLERANT, as a data quality professional, knows what a Herculean task clean data can be. That is why we have developed special tools for this task.
Top 10: Best practice data migration
EditorialMigrating data from multiple sources into a new information management system is a complex and often headache-inducing undertaking. Data migration is usually necessary to keep pace with technological advances and industry standards, but it requires a great deal of effort. Data from different storage areas – both on-premises and in the cloud – must be evaluated, analyzed, cleansed and organized before it can be combined and matched.