How To Fix RSD_TREX433 - Deviation in average of attribute &1 from table &2 for DB and BWA


RSD_TREX433 - Overview

  • Message type: E = Error

  • Message class: RSD_TREX - Messages from TREX Aggregate Area

  • Message number: 433

  • Message text: Deviation in average of attribute &1 from table &2 for DB and BWA

  • Show details Hide details
  • What causes this issue?

    The average of the attribute <(>&<)>1 of table <(>&<)>2 was calculated
    from the values that are saved in the BWA and on the database,
    respectively. The two average values were compared. During the
    comparison, a large deviation was found. This deviation exceeds the
    tolerances that are given for the float fields due to inconsistencies.

    The system issues an error message and will not allow you to continue with this transaction until the error is resolved.

    System Response

    How to fix this error?

    Procedure for System Administrators


    Error message extract from SAP system. Copyright SAP SE.


Smart SAP Assistant

  • What is the cause and solution for SAP error message RSD_TREX433 - Deviation in average of attribute &1 from table &2 for DB and BWA ?
    The SAP error message RSD_TREX433 indicates a deviation in the average of an attribute from a table in the database (DB) and the Business Warehouse Accelerator (BWA). This error typically arises during the data loading or reporting processes in SAP BW when there is a mismatch between the data stored in the database and the data in the BWA.
    
    Cause: Data Inconsistency: The most common cause of this error is that the data in the database and the data in the BWA are not synchronized. This can happen if there were changes made to the data in the database that were not reflected in the BWA. Data Load Issues: If there were issues during the data load process, such as incomplete loads or errors, this could lead to discrepancies. Aggregation Issues: If the aggregation settings for the attribute are not correctly configured, it may lead to differences in the calculated averages. Data Modeling Issues: Incorrect

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