How To Fix /CCEE/SIFIDDV001 - Data saved successfully (check log for details).

/CCEE/SIFIDDV001 - Overview

• Message type: E = Error

• Message class: /CCEE/SIFIDDV -

• Message number: 001

• Message text: Data saved successfully (check log for details).

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 /CCEE/SIFIDDV001 - Data saved successfully (check log for details). ?

  The SAP error message /CCEE/SIFIDDV001 Data saved successfully (check log for details) typically indicates that while the data was saved, there may have been issues or warnings during the process that need to be reviewed in the logs for further details. This message is often associated with the SAP Customer Experience (CX) or SAP Commerce Cloud environments, particularly in the context of data import or synchronization processes.
  
  Cause:
  
  Warnings or Errors During Processing: The data was saved, but there may have been warnings or errors that occurred during the validation or processing of the data.
  Data Integrity Issues: There could be issues related to data integrity, such as missing mandatory fields, incorrect data formats, or relationships between data entities that were not satisfied.
  
  Configuration Issues: There may be configuration settings in the system that are not aligned with the data being processed, leading to warnings.
  Business Logic Violations: The data might have violated certain business