Tag: TOLERANT Match - Page 1

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In a podcast interview, TOLERANT Software Managing Director Stefan Sedlacek revealed how fault-tolerant search works in data quality tools and the technology behind it. The podcast interview was conducted by Ashley Steele. You can read an excerpt from the interview here.

TOLERANT Software uses AI-based associative memory technology for the error-tolerant search for duplicates. The TL Match data quality tool from TOLERANT Software thus finds duplicate data records even if they are spelt differently.

The half-life of customer data is seven years on average. This means that after seven years, half of the data is already out of date, for example because customers have moved house, got married or taken out a new telephone contract. The data quality tools TL Match, TL Post, TL Name, TL Move and TL Bank from TOLERANT Software considerably increase the half-life of customer data.

The duplicate checking tool TL Match has been released in a new product version. The release TL Match 11.2 provides the user with a more flexible license design and new options for field assignment. Among other things, 429 million different single values can now be mapped and searched sharply. That is more than 16 times as many values as in the previous version of TL Match.

TOLERANT Software, the Stuttgart-based specialist for data quality tools, has completely revised two of its tools. The address validation tool TL Post and the duplicate check tool TL Match can now be centrally managed in a portal and easily integrated into cloud environments. A modernised user interface facilitates operation.

Since May 25, 2018, the new General Data Protection Regulation of the European Union, or EU-GDPR for short, applies and with it a new and extended right to information. According to Article 15 of the GDPR, data subjects have the right to receive confirmation from data controllers as to whether personal data are being processed.

TOLERANT Match is our standard product for fast-as-an-arrow, accurate customer search and duplicate detection in large databases.

Not likely. You want to address your customers correctly. This starts with the correct and full spelling of the name, and ends with a correct, deliverable postal address. Duplicate salutations caused by duplicates in the database can be embarrassing.

Some may see data migration as a chore when introducing new IT systems. However, it is exactly the opposite: Data migration is a great opportunity to systematically cleanse and reprocess data and, if necessary, enrich it with external data.

The 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.