How To Fix /FLDQ/AD_TECH_ERRORS911 - Insufficient or excess records returned from Data Services.

SAP Error Message - Details

• Message type: E = Error

• Message class: /FLDQ/AD_TECH_ERRORS -

• Message number: 911

• Message text: Insufficient or excess records returned from Data Services.

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message /FLDQ/AD_TECH_ERRORS911 - Insufficient or excess records returned from Data Services. ?

  The SAP error message /FLDQ/AD_TECH_ERRORS911 indicating "Insufficient or excess records returned from Data Services" typically arises in the context of data extraction or data loading processes, particularly when using SAP Data Services (DS) or SAP Data Intelligence. This error suggests that the number of records returned from a data source does not match the expected number of records defined in the job or data flow.
  Causes:
  
  
  Mismatch in Record Count: The number of records returned from the source does not match the expected count defined in the job configuration. This could be due to:
  
  Filters applied in the data flow that limit the number of records.
  Changes in the source data that result in fewer or more records than anticipated.
  
  
  
  Data Quality Issues: There may be issues with the data itself, such as:
  
  Missing records.
  Duplicates or unexpected data formats that cause the data flow to behave unexpectedly.
  
  
  
  Configuration Errors: Incorrect settings in the job or data flow configuration can lead to this error. This includes:
  
  Incorrect source or target definitions.
  Misconfigured transformations or mappings.
  
  
  
  Network or Connectivity Issues: Temporary issues with the connection to the data source can lead to incomplete data retrieval.
  
  
  Solutions:
  
  
  Review Job Configuration: Check the job or data flow configuration to ensure that the expected record count is correctly defined. Adjust any filters or conditions that may be limiting the data.
  
  
  Validate Source Data: Examine the source data to ensure that it contains the expected number of records. Look for any changes in the data that may have occurred since the last successful run.
  
  
  Check Data Quality: Implement data quality checks to identify and resolve issues with missing or duplicate records. This may involve cleansing the data or adjusting the data flow to handle exceptions.
  
  
  Adjust Error Handling: Modify the error handling settings in the job to allow for a wider range of acceptable record counts, if appropriate for your use case.
  
  
  Test Connectivity: Ensure that there are no connectivity issues with the data source. Test the connection and verify that the data can be accessed without issues.
  
  
  Consult Logs: Review the logs generated by SAP Data Services for more detailed error messages or warnings that can provide additional context for the issue.
  
  
  Related Information:
  
  SAP Documentation: Refer to the official SAP documentation for Data Services and Data Intelligence for detailed guidance on error handling and troubleshooting.
  SAP Community: Engage with the SAP Community forums to seek advice from other users who may have encountered similar issues.
  Data Services Best Practices: Familiarize yourself with best practices for data extraction and loading processes to minimize the occurrence of such errors in the future.
  
  By following these steps, you should be able to identify the root cause of the error and implement a suitable solution.