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Message type: E = Error
Message class: CNV_DMC_SIN - Messages for s-innovations migration
Message number: 444
Message text: &1 are from type person, but org data are filled at sheet/table &2
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CNV_DMC_SIN444
- &1 are from type person, but org data are filled at sheet/table &2 ?The SAP error message CNV_DMC_SIN444 typically occurs during data migration processes, particularly when using the SAP Data Migration Cockpit (DMC) or similar tools. This error indicates a mismatch between the type of data being processed and the organizational data that has been filled in the specified sheet or table.
Cause:
The error message suggests that the system is expecting data of a certain type (in this case, "person") but has found organizational data filled in the specified sheet or table. This can happen due to several reasons:
- Data Mapping Issues: The data being imported does not match the expected structure or type defined in the migration template.
- Incorrect Template Usage: The wrong template may have been used for the data migration, leading to a mismatch in the expected data types.
- Data Entry Errors: There may be incorrect entries in the migration sheet, where organizational data has been mistakenly entered in a field meant for person data.
Solution:
To resolve this error, you can take the following steps:
- Review the Migration Template: Ensure that you are using the correct migration template that corresponds to the type of data you are trying to import.
- Check Data Entries: Go through the entries in the specified sheet/table and verify that the data types match the expected format. Ensure that person-related fields are filled with appropriate data and that organizational data is placed in the correct fields.
- Data Mapping Configuration: If you are using a mapping configuration, check that it is set up correctly to map person data to the appropriate fields.
- Consult Documentation: Refer to the SAP documentation for the specific migration process you are using to ensure compliance with the required data structure.
- Testing: If possible, run a test migration with a smaller dataset to identify any issues before performing a full migration.
Related Information:
By following these steps, you should be able to identify the cause of the error and implement a solution to resolve it.
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