How To Fix RSL_UI321 - &1 rows have been cleansed

SAP Error Message - Details

• Message type: E = Error

• Message class: RSL_UI -

• Message number: 321

• Message text: &1 rows have been cleansed

Self-Explanatory Message

Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.

To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

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Smart SAP Assistant

• What is the cause and solution for SAP error message RSL_UI321 - &1 rows have been cleansed ?

  The SAP error message RSL_UI321 indicates that a certain number of rows have been cleansed during a data processing operation, typically related to data quality or data cleansing tasks. This message is often encountered in the context of SAP Data Services or SAP Information Steward, where data is being validated, transformed, or cleansed.
  Cause:
  The message indicates that the system has identified and removed or modified rows of data that did not meet certain quality criteria. This could be due to various reasons, such as:
  
  Missing required fields
  Invalid data formats
  Duplicates
  Data that does not conform to business rules or standards
  
  Solution:
  To address the RSL_UI321 message, consider the following steps:
  
  
  Review the Cleansing Rules: Check the data cleansing rules that are applied to the dataset. Ensure that they are appropriate for the data you are processing.
  
  
  Analyze the Cleansed Data: Look into the details of the rows that were cleansed. This may involve checking logs or reports generated by the data processing job to understand why those rows were affected.
  
  
  Adjust Data Quality Rules: If the cleansing rules are too strict or not aligned with your business requirements, consider adjusting them to allow more data to pass through without being cleansed.
  
  
  Data Validation: Ensure that the data being input into the system is validated before processing. This can help reduce the number of rows that are cleansed.
  
  
  Consult Documentation: Refer to SAP documentation or help resources for specific guidance on the cleansing process and how to interpret the cleansing results.
  
  
  Testing: After making adjustments, run tests with a sample of your data to see if the changes have the desired effect.
  
  
  Related Information:
  
  SAP Data Services: This tool is often used for data integration and transformation, and it includes features for data cleansing.
  SAP Information Steward: This tool provides data quality management capabilities, including monitoring and improving data quality.
  Data Quality Framework: Understanding the framework and best practices for maintaining data quality in SAP systems can help prevent issues like this in the future.
  
  If the issue persists or if you need more specific guidance, consider reaching out to SAP support or consulting with a data management expert familiar with your specific SAP environment.