How To Fix CNV_PE395 - Invalid date &1 passed

SAP Error Message - Details

• Message type: E = Error

• Message class: CNV_PE - General messages for posting engine

• Message number: 395

• Message text: Invalid date &1 passed

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message CNV_PE395 - Invalid date &1 passed ?

  The SAP error message CNV_PE395 Invalid date &1 passed typically occurs during data migration or conversion processes, particularly when using the SAP Landscape Transformation (SLT) or other data migration tools. This error indicates that an invalid date format or an out-of-range date value has been encountered in the data being processed.
  Cause:
  
  Invalid Date Format: The date provided does not conform to the expected format (e.g., YYYY-MM-DD).
  Out-of-Range Dates: The date value is outside the acceptable range for the SAP system (e.g., dates before 1970 or after 2038).
  Data Type Mismatch: The field expecting a date value may be receiving a different data type (e.g., a string or numeric value).
  Incorrect Mapping: During data migration, the mapping of fields may not be correctly defined, leading to invalid data being passed.
  
  Solution:
  
  Check Date Format: Ensure that the date values being passed conform to the expected format. For SAP, the standard format is typically YYYY-MM-DD.
  Validate Date Values: Review the data being processed to ensure that all date values are within the acceptable range for the SAP system.
  Data Type Verification: Confirm that the data types in the source and target systems match, especially for date fields.
  Review Mapping Configuration: If using a data migration tool, check the mapping configuration to ensure that date fields are correctly mapped and that no invalid values are being passed.
  Data Cleansing: If necessary, cleanse the data before migration to remove or correct invalid date entries.
  
  Related Information:
  
  SAP Notes: Check for any relevant SAP Notes or documentation that may provide additional context or solutions for this error.
  Transaction Codes: Use transaction codes like SE11 (Data Dictionary) or SE16 (Data Browser) to inspect the data structures and validate the data types.
  Testing: Perform tests with a smaller dataset to isolate the issue and verify that the changes made resolve the error before attempting a full migration.
  
  If the problem persists after following these steps, it may be beneficial to consult with SAP support or a technical consultant who specializes in data migration processes.