How To Fix RSL_UI342 - &2 data rows cleansed out of a total of &1

SAP Error Message - Details

• Message type: E = Error

• Message class: RSL_UI -

• Message number: 342

• Message text: &2 data rows cleansed out of a total of &1

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message RSL_UI342 - &2 data rows cleansed out of a total of &1 ?

  The SAP error message RSL_UI342 indicates that during a data cleansing operation, a certain number of data rows were removed from a total set of rows. The message format typically looks like this: "RSL_UI342 &2 data rows cleansed out of a total of &1," where "&1" represents the total number of rows processed and "&2" represents the number of rows that were cleansed (i.e., removed or flagged for issues).
  Cause:
  The primary cause of this error message is that the data cleansing process has identified certain rows in the dataset that do not meet the required quality standards or criteria set for the data. This could be due to various reasons, such as:
  
  Data Quality Issues: The rows may contain invalid, incomplete, or inconsistent data.
  Business Rules Violations: The data may not comply with specific business rules or validation checks defined in the system.
  Duplicate Records: The cleansing process may have identified duplicate entries that need to be removed.
  Format Issues: Data may not be in the expected format (e.g., date formats, numeric formats).
  
  Solution:
  To address the RSL_UI342 error message, consider the following steps:
  
  Review Cleansing Rules: Check the data cleansing rules and criteria that are applied. Ensure that they are appropriate for the data you are processing.
  Analyze Cleansed Data: Look into the specific rows that were cleansed (removed) to understand why they were flagged. This may involve reviewing logs or reports generated during the cleansing process.
  Data Correction: If possible, correct the data issues in the original dataset before re-running the cleansing process. This may involve fixing formatting issues, removing duplicates, or filling in missing values.
  Adjust Parameters: If the cleansing process is too aggressive, consider adjusting the parameters or thresholds used for cleansing to retain more data while still ensuring quality.
  Consult Documentation: Refer to SAP documentation or support resources for specific guidance related to the data cleansing tool or module you are using.
  
  Related Information:
  
  SAP Data Cleansing Tools: Familiarize yourself with the specific SAP tools or modules you are using for data cleansing, such as SAP Data Services or SAP Information Steward.
  Data Quality Management: Understanding data quality management principles can help in setting up effective cleansing processes.
  Error Logs: Check for any additional error logs or messages that may provide more context about the cleansing operation and the specific issues encountered.
  
  If the problem persists after following these steps, consider reaching out to SAP support or consulting with a professional who specializes in SAP data management for further assistance.