How to use CNV_20100_CHK_FLD - Analyze new account/cost el. fields


SAP Transaction Code - Details

  • Transaction Code: CNV_20100_CHK_FLD

    Description: Analyze new account/cost el. fields

    Release: S/4HANA and ECC 6

  • Show technical details Hide technical details
    • Program:

      Screen: 0

      Authorization Object:

    • Development Package: CNV_20100

      Package Description: CNCC: Chart of accounts conversion

      Parent Package: DMIS_APPL_CNV_CONV

    • Module/Component: CA-DT-CNV

      Description: Landscape Transformation for Conversion


Smart SAP Assistant

  • SAP Tcode: CNV_20100_CHK_FLD - Analyze new account/cost el. fields
    
    Overview: 
    CNV_20100_CHK_FLD is a SAP transaction code used to analyze new account/cost element fields. It is used to check the consistency of the data in the fields and to ensure that the data is correctly entered. 
    
    Functionality: 
    This transaction code allows users to check the consistency of the data in the new account/cost element fields. It can be used to check for errors in the data, such as incorrect values or missing information. The transaction code also allows users to view a list of all the fields that have been changed and to compare them with the original values. 
    
    Step-by-step How to Use: 
    1. Enter CNV_20100_CHK_FLD into the SAP command field. 
    2. Select “Execute” to open the transaction code. 
    3. Select “Check” to begin analyzing the new account/cost element fields. 
    4. Review the list of changed fields and compare them with the original values. 
    5. If any errors are found, make corrections as necessary. 
    6. Select “Save” to save your changes and exit the transaction code. 
    
    Other Recommendations: 
    It is recommended that users regularly use this transaction code to check for errors in their data entries and ensure that all information is accurate and up-to-date. Additionally, users should always back up their data before making any changes, as this will help prevent any potential data loss or corruption.
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