How To Fix RSSDA113 - DataSource field &1 must be numeric

SAP Error Message - Details

• Message type: E = Error

• Message class: RSSDA - BW HANA Smart Data Access

• Message number: 113

• Message text: DataSource field &1 must be numeric

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 RSSDA113 - DataSource field &1 must be numeric ?

  The SAP error message RSSDA113 indicates that a specific field in a DataSource is expected to contain numeric data, but the value provided is not numeric. This error typically occurs during data extraction or data loading processes, particularly when working with SAP BW (Business Warehouse) or SAP Data Services.
  
  Cause:
  
  Data Type Mismatch: The field in question is defined as a numeric type in the DataSource, but the incoming data contains non-numeric characters (e.g., letters, special characters).
  Incorrect Mapping: The mapping of fields between the source system and the DataSource may be incorrect, leading to non-numeric data being placed in a numeric field.
  Data Quality Issues: The source data may contain invalid entries or formatting issues that prevent it from being recognized as numeric.
  
  
  Solution:
  
  Check Data Source: Review the source data to ensure that the values for the specified field are indeed numeric. Look for any non-numeric characters or formatting issues.
  Data Transformation: If you are