How To Fix /FLDQ/AD_TECH_ERRORS563 - Dataflow error message returned from Data Services.

/FLDQ/AD_TECH_ERRORS563 - Overview

• Message type: E = Error

• Message class: /FLDQ/AD_TECH_ERRORS -

• Message number: 563

• Message text: Dataflow error message returned from Data Services.

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?

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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.

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Smart SAP Assistant

• What is the cause and solution for SAP error message /FLDQ/AD_TECH_ERRORS563 - Dataflow error message returned from Data Services. ?

  The SAP error message /FLDQ/AD_TECH_ERRORS563 typically indicates a dataflow error in SAP Data Services. This error can arise from various issues during the data extraction, transformation, or loading processes. Here are some common causes, potential solutions, and related information:
  Causes:
  
  Data Type Mismatch: The data being processed may not match the expected data types defined in the target schema.
  Null Values: The dataflow may be encountering unexpected null values that are not handled properly.
  Transformation Logic Errors: There may be issues in the transformation logic, such as incorrect expressions or functions.
  Source Data Issues: Problems with the source data, such as missing records or corrupted data, can lead to errors.
  Connection Issues: Problems with the connection to the source or target systems can also trigger this error.
  Resource Limitations: Insufficient memory or processing power on the Data Services server can lead to failures in processing.
  
  Solutions:
  
  Check Data Types: Review the data types in the source and target schemas