Duplicate-Check — Clean and find duplicates

Clean and find duplicates

Do you want to clean up your addresses, find duplicate records and thus achieve a higher quality of your master data? You can clean all your existing addresses in your master data with the Duplicate-Check software. Find duplicate records easily. Transfer them to your CRM system or ERP system.

    Duplicate-Check
    Duplicate-Check

    Function overview Duplicate-Check

    Import formats

    • CSV
    • JSON
    • XLSX (Microsoft Excel)

    Cleanup

    • Cleanup of typos and “superfluous” characters
    • Standardization of information such as “street” or company name
    • Separation of fields for data transfers

    Duplicates

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

    You can test the software first even without a valid license. In the trial version, the first 100 data records are checked.

    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 software. Whether we can solve all cases with it, your feedback will show.

    Mode of operation

    The duplicate check process is shown below. Unless configured otherwise, it always proceeds according to the following scheme:

    • normalization
    • duplicate check

    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 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.

    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.

    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

    Using batch processing, you can set up a CSV, JSON or XLSX export from your ERP system. You can then have all the master data contained in it checked directly with the duplicate check.

    Select the file to be imported or drag and drop it onto the Duplicate-Check 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 for Duplicate-Check

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

    If you have further questions, feel free to have a look at our documentation. If you still have questions, contact us.