How To Fix RS_DB_DB6038 - Number of different values in MDC dimension &1: &2

SAP Error Message - Details

• Message type: E = Error

• Message class: RS_DB_DB6 - DB6-Specific Messages in SAP BW

• Message number: 038

• Message text: Number of different values in MDC dimension &1: &2

Self-Explanatory Message

Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.

To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

Unfortunately, there isn't any extra information in this error notice.

What else can you do?

First, use our AnswerBot below to get a possible cause and solution (requires a premium subscription).

Also, review the in-depth Common Questions & Answers listed below; you could discover a solution there or be able to connect with others who have faced similar challenges.

You can also try searching the SAP support portal (support.sap.com) but you need a special user ID to access it. It is possible that an SAP support note exists that provides additional details about the mistake or even steps for fixing it.

Smart SAP Assistant

• What is the cause and solution for SAP error message RS_DB_DB6038 - Number of different values in MDC dimension &1: &2 ?

  The SAP error message RS_DB_DB6038 typically indicates that there is a mismatch in the number of different values in a Multi-Dimensional Cube (MDC) dimension. This error can occur during data loading or when processing queries in SAP BW (Business Warehouse) or SAP HANA environments.
  
  Cause:
  The error message RS_DB_DB6038 is triggered when the number of distinct values in a dimension does not match the expected number of distinct values. This can happen due to several reasons, including:
  
  Data Inconsistency: The data being loaded into the cube may have inconsistencies or duplicates that lead to a mismatch in the expected values.
  Changes in Data Source: If the underlying data source has changed (e.g., new values added, existing values modified or deleted), it can lead to discrepancies in the dimension values.
  Incorrect Data Modeling: The data model may not be correctly defined, leading to issues in how dimensions are populated.
  Data Transformation Issues: During the ETL (Extract, Transform,