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Message type: E = Error
Message class: CM_MDQLTYRULEMINING - Messages for Rule Mining Run
Message number: 022
Message text: Field value for table &1, field &2, and table &3, field &4 must be same.
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CM_MDQLTYRULEMINING022
- Field value for table &1, field &2, and table &3, field &4 must be same. ?The SAP error message CM_MDQLTYRULEMINING022 indicates that there is a mismatch in the values of specific fields across different tables. This error typically arises in the context of data quality rules or data mining processes where consistency between related data entries is crucial.
Cause:
The error occurs when the system detects that the value in a specified field of one table does not match the value in a corresponding field of another table. This inconsistency can happen due to various reasons, such as:
- Data Entry Errors: Manual data entry mistakes can lead to discrepancies between related fields.
- Data Migration Issues: During data migration or integration processes, data may not have been transferred correctly, leading to mismatches.
- Business Logic Violations: The business rules defined in the system may not have been adhered to, resulting in inconsistent data.
- System Configuration Issues: Incorrect configuration of data quality rules or relationships between tables can lead to this error.
Solution:
To resolve the CM_MDQLTYRULEMINING022 error, you can follow these steps:
Identify the Tables and Fields: Review the error message to identify the specific tables and fields involved in the mismatch. The message will specify the names of the tables and fields (e.g., &1, &2, &3, &4).
Check Data Consistency:
- Query the relevant tables to check the values in the specified fields.
- Compare the values to identify discrepancies.
Correct the Data:
- If you find inconsistencies, update the records in the affected tables to ensure that the values in the specified fields match.
- Ensure that any changes made are in line with business rules and data integrity requirements.
Review Data Quality Rules:
- If applicable, review the data quality rules that triggered the error to ensure they are correctly defined and aligned with business processes.
Test the Changes: After making corrections, re-run the process that triggered the error to confirm that the issue has been resolved.
Documentation and Training: If the error was caused by user input, consider providing additional training or documentation to prevent similar issues in the future.
Related Information:
By following these steps, you should be able to identify the root cause of the error and implement a solution to ensure data consistency across the specified fields.
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