How to use MCSR - Análisis estándar dat. externos

MCSR - Overview

• Transaction Code: MCSR

  Description: Análisis estándar dat. externos

  Release: S/4HANA and ECC 6

  Menu Path:

  • Logistics > Production > Kanban > Environment > Warehouse Management > Environment > Rough workload estimate > Logistics Information System > Standard Analyses > External Data
  • Logistics > Logistics Controlling > Logistics Information System > Standard Analyses > External Data

• • Program: SAPMMCS4

    Screen: 100

    Authorization Object:

  • Development Package: MCS

    Package Description: R/3 application development: Logistics Information Warehouse

    Parent Package: APPL

  • Module/Component: LO-LIS-DC

    Description: Data Collection

MCSR - Details

• SAP Tcode: MCSR - Análisis estándar dat. externos

  
  Overview: 
  MCSR is a SAP transaction code used to analyze external data. It is used to compare and analyze data from different sources, such as external databases, spreadsheets, and other sources. This transaction code is part of the SAP Business Warehouse (BW) system. 
  
  Functionality: 
  MCSR enables users to compare and analyze data from different sources. It allows users to create reports and charts that can be used for further analysis. The data can be filtered and sorted according to various criteria, such as date, time, or other parameters. The results of the analysis can be used to make decisions or take action. 
  
  Step-by-step How to Use: 
  1. Log into the SAP system and enter the transaction code MCSR. 
  2. Select the source of the data you want to analyze. 
  3. Enter the criteria for filtering and sorting the data. 
  4. Select the type of report or chart you want to generate. 
  5. Generate the report or chart and view the results of your analysis. 
  6. Take action based on your findings or save the report for future reference. 
  
  Other Recommendations: 
  It is recommended that users familiarize themselves with the features of MCSR before using it for analysis purposes. Additionally, users should ensure that they have access to all necessary data sources before beginning their analysis. Finally, users should always review their results carefully before taking