How to use WAHD1 - Load Alternative Historical Data

SAP Transaction Code - Details

• Transaction Code: WAHD1

  Description: Load Alternative Historical Data

  Release: S/4HANA and ECC 6

• • Program: RWAHD001

    Screen: 1000

    Authorization Object:

  • Development Package: WEFF

    Package Description:

    Parent Package:

  • Module/Component:

    Description:

Smart SAP Assistant

• SAP Tcode: WAHD1 - Load Alternative Historical Data

  
  Overview:
  The SAP transaction code WAHD1 is used to load alternative historical data into the system. This data can be used to analyze and compare different scenarios and make decisions based on the results. The data is stored in a separate table and can be accessed through the transaction code. 
  
  Functionality: 
  The WAHD1 transaction code allows users to load alternative historical data into the system. This data can be used to analyze different scenarios and make decisions based on the results. The data is stored in a separate table and can be accessed through the transaction code. The data can also be used for reporting purposes. 
  
  Step-by-Step How to Use 
  1. Enter the transaction code WAHD1 in the command field. 
  2. Select the “Load Alternative Historical Data” option from the menu. 
  3. Enter the name of the table where you want to store the data. 
  4. Select the type of data you want to load (e.g., sales, inventory, etc.). 
  5. Enter the date range for which you want to load the data (e.g., last month, last year, etc.). 
  6. Select the fields you want to include in your report (e.g., customer name, product name, etc.). 
  7. Click “Execute” to start loading the data into the system. 
  8. Once the loading is complete, you can view and analyze the data using other SAP tools such as SAP BusinessObjects or SAP Lumira. 
  
  Other Recommendations: 
  It is recommended that users back up their data before loading it into the system using WAHD1 transaction code. This will ensure that any changes made to the data are not lost if something goes wrong during loading or analysis process. Additionally, users should also ensure that they have sufficient disk space available before loading large amounts of data into the system as this could cause performance issues if not managed properly.