Duplicate Check: Clean Addresses and find duplicates

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 your existing addresses in your master data and conveniently find duplicate entries and import them into your existing ERP system.

Overview of the module Duplicate Check

ID Validation - Module ‘Duplicate check’ Clean addresses and find duplicates

Clean up

  • Cleaning up typos and “superfluous” characters.
  • Standardization of data, such as “street” or company name
  • Separation of fields for data transfers

Duplicates

  • Finding duplicate entries (deduplication)
  • Finding similar entries or swapped entries
  • Rule-based checking

Why should you clean up your addresses?

Typing errors, name changes or the merging of several address databases (e.g. by consolidating applications) can lead to duplicate or incorrect addresses. Not only an inaccurate number of actual addresses, but also erroneous addresses due to mailing or duplicate mailing of documents can cause an evaluation or higher costs. In our many years of experience in the ERP application environment, we have often come into contact with these issues and have more than once performed a cleanup individually. We would now like to try to consolidate this with this module. Whether we can solve all cases with it, your feedback will show.

Licencing

You are already a customer of ours and use the ID Validation? Then you get this module for free! You can also test the module first without a valid license. However, not all rules and checks are available in the test version.

Mode of operation

1. normalization of the data

We disassemble and reassemble your data. For example, we recognize the difference between GmBH and GmbH, u. Co. KG and & Co. KG. A street is a street and also a street without a dot and a street with a dot.

After normalization, we have a street in which a GmbH & Co. KG trades.

ID Validation - Module ‘Duplicate Check’ - Cleaner

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

2. rule-based duplicate check

There is a large number of fields, such as Company, Name, Name1, Name2, Addition, Street with and Street without house number, etc.

ID Validation - Module ‘Duplicate Check’ - Rules

Depending on the selected rules, the following examples are different or identical companies, or yet only one department:

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. batch processing

With the help of batch processing, you can set up a CSV, JSON or XLSX export from your ERP system and then have all the master data it contains checked directly with the duplicate check.

ID Validation - Module ‘Duplicate Check’ - Batch Processing

Select the file to be imported or drag and drop it onto the ID Validation and you can check the entire file. After a relatively short time you will have checked each record for existing duplicates or cleaned the record.

4. your decision

We will only provide you with the overview, if necessary also 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 hand them over to those responsible for master data management.

Notes

We assume no liability for any data loss that may occur due to the use of the Duplicate Check module.