How To Fix RS_HCPR_MODEL103 - Aggregation '&2' of key figure &1 is not possible

RS_HCPR_MODEL103 - Overview

• Message type: E = Error

• Message class: RS_HCPR_MODEL - Messages related to the HANA Composite Provider Backend

• Message number: 103

• Message text: Aggregation '&2' of key figure &1 is not possible

What causes this issue?

Aggregation for key figures is not possible in the modeled
CompositeProvider. For this kind of key figure, aggregation is not
allowed in the CompositeProvider. Aggregation is only possible, for
example, if all navigation attributes are available in the
PartProviders, no joins are modeled in the CompositeProvider or no SAP
HANA models are used as PartProviders.

System Response

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

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 RS_HCPR_MODEL103 - Aggregation '&2' of key figure &1 is not possible ?

  The SAP error message RS_HCPR_MODEL103 indicates that there is an issue with the aggregation of a key figure in a data model, typically in the context of SAP BW (Business Warehouse) or SAP HANA. The message states that the specified aggregation for the key figure is not possible, which can occur due to various reasons.
  Causes:
  
  
  Incompatible Aggregation Type: The aggregation type defined for the key figure may not be compatible with the data type or the nature of the data being aggregated. For example, trying to sum up a key figure that is not numeric.
  
  
  Missing Data: If the data required for the aggregation is missing or not loaded properly, the aggregation cannot be performed.
  
  
  Incorrect Configuration: The configuration settings for the InfoObject or the aggregation level may be incorrect, leading to issues in how the data is aggregated.
  
  
  Data Model Issues: There may be issues with the underlying data model, such as incorrect