How To Fix IFME_ENGINE130 - Missing column in source data

SAP Error Message - Details

• Message type: E = Error

• Message class: IFME_ENGINE - Incoming files - Engine

• Message number: 130

• Message text: Missing column in source data

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 IFME_ENGINE130 - Missing column in source data ?

  The SAP error message IFME_ENGINE130: Missing column in source data typically occurs in the context of data processing or data extraction, particularly when using SAP's Information Management or ETL (Extract, Transform, Load) tools. This error indicates that a required column in the source data is not present, which can prevent the successful execution of a data operation.
  Causes:
  
  Schema Mismatch: The source data structure has changed, and the expected column is no longer present.
  Incorrect Data Source: The wrong data source may have been selected, which does not contain the required columns.
  Data Extraction Issues: There may be issues with the data extraction process that resulted in missing columns.
  Configuration Errors: The configuration settings in the data processing job may not align with the actual structure of the source data.
  Data Quality Issues: The source data may have been corrupted or improperly formatted, leading to missing columns.
  
  Solutions:
  
  Verify Source Data Structure: Check the source data to ensure that all required columns are present. Compare the current structure with the expected schema.
  Update Data Source: If the source data has changed, update the data extraction or processing job to reflect the new structure.
  Check Configuration Settings: Review the configuration settings in the ETL job or data processing tool to ensure they match the current source data structure.
  Data Validation: Implement data validation checks to ensure that the source data meets the required schema before processing.
  Error Handling: Implement error handling in your data processing logic to gracefully manage missing columns and provide informative error messages.
  
  Related Information:
  
  Documentation: Refer to SAP documentation for the specific module or tool you are using (e.g., SAP Data Services, SAP BW) for detailed information on data structure requirements.
  SAP Notes: Check SAP Notes for any known issues or patches related to this error message.
  Community Forums: Engage with SAP community forums or support channels for insights from other users who may have encountered similar issues.
  Testing: Conduct tests with sample data to ensure that the data processing job works as expected before running it on production data.
  
  By following these steps, you should be able to identify the cause of the error and implement a solution to resolve it.