How to use GJGA - Display JOA graphically


SAP Transaction Code - Details

  • Transaction Code: GJGA

    Description: Display JOA graphically

    Release: S/4HANA and ECC 6

    Menu Path:

    • Accounting > Joint Venture Accounting > Information System > Master Data > Display JOA Graphic
  • Show technical details Hide technical details
    • Program: RGJGRA01

      Screen: 1000

      Authorization Object:

    • Development Package: GJVA

      Package Description:

      Parent Package: JVA_JV

    • Module/Component: CA-JVA

      Description: Joint Venture und Production Sharing Accounting


Smart SAP Assistant

  • SAP Tcode: GJGA - Display JOA graphically
    
    Overview:
    The SAP transaction code GJGA is used to display the Job Order Analysis (JOA) graphically. This code is used to view the job order analysis in a graphical format, which can be used to analyze the job order data and identify any potential issues. 
    
    Functionality: 
    The GJGA transaction code allows users to view the job order analysis in a graphical format. This graphical representation of the job order data can be used to identify any potential issues or trends in the data. The graphical representation also allows users to quickly identify any outliers or discrepancies in the data. 
    
    Step-by-step How to Use: 
    1. Enter the transaction code GJGA into the command field. 
    2. Select the appropriate plant and period for which you want to view the job order analysis. 
    3. Select the type of graph you want to view (bar chart, line chart, etc.). 
    4. Select the type of data you want to view (quantity, cost, etc.). 
    5. Select any additional options you want to include in your graph (trend lines, etc.). 
    6. Click “Execute” to generate your graph. 
    7. View and analyze your graph for any potential issues or trends in your job order data. 
    
    Other Recommendations: 
    It is recommended that users save their graphs for future reference and comparison purposes. Additionally, users should take note of any outliers or discrepancies in their data and investigate further if necessary.
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