Clean Addresses - Duplicate Check Module

soon available/free of charge for all existing customers

Do you want to clean up your addresses, find duplicates and thus achieve a higher quality of your master data?

You can use the Duplicate Check module to clean up all existing addresses in your master data and duplicate entries easily find out and install it into your existing ERP system.

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Overview of the module “Duplicate Check”

  • Clean up typos and “superfluous” characters
  • Separation of fields for data transfers
  • Finding duplicate entries (deduplicating)
  • Standardization of information such as “road” or company name
  • Finding similar entries or exchanged entries
  • Rule-based testing

Why should you clean up your addresses?

Typo errors, renaming or merging of multiple address databases (e.g. by consolidating applications) can lead to duplicate or incorrect Maintain addresses. Not only an inaccurate number of actual addresses, but also miseres through mailing or duplicate sending of documents can be evaluated or higher costs. In our many years of experience in the ERP application environment, we have often come into contact with these topics and have more than once a Cleanup carried out individually. Now we want to try to consolidate this with this module. Your feedback will show whether we can solve all cases with it.

This module will be released in the coming weeks. Would you like to be informed by us as soon as we have an exact date for this module, subscribe to our Newsletter.

You are already a customer of us and use the ID Validation? Then you get this module free!

Mode of operation

1. normalization of the data

We decompose and reassemble your data. For example, we recognize the difference between LTD. and Ltd.. A street is a street and also a Str without point and a Str. with point.

After normalization we have a street in which a Ltd. is trading.

Using this example, which is only one of many, we bring your data into the correct format. This will make the next step easier.

2. rule-based duplicate check

There are a large number of fields, such as company, name, name1, name2, addition, street with and street without house number, etc.

Depending on the selected rules, the following examples are different or identical companies, or just one department after all:

correct address

Sample Company Ltd.  
Sample Street 1    
12345 Sample Village

same address with department

Sample Company Ltd.
Controlling
Sample Street 1
12345 Sample Village

same address with department and misspelling.

Sample Company Ltd.
Controlling
Sample Street 1
12345 Sample Vllage

3. your decision

We will only provide you with the overview, if necessary also with the cleaned data in the same form as your imported file. Now you can decide. If you use Microsoft Excel, you can filter the data according to rules, view the results and pass them to your responsible persons of the master data management.

Notes

We assume no liability for any loss of data due to the use of the module “Duplicate Check”.