Error
Error Code:
4678
SAP S/4HANA Error 4678: Invalid Data Flow Configuration
Description
This error indicates that a data provisioning process within SAP S/4HANA encountered an invalid or improperly defined data flow. It typically occurs during data replication, integration, or transformation activities where the defined path for data movement is not viable or correctly configured.
Error Message
ERR_DATAPROV_INVALID_DATAFLOW
Known Causes
4 known causesMismatched Data Schemas
The data structure (schema) of the source system does not align with the expected structure of the target system in the data flow.
Incorrect Data Flow Definition
The data flow was configured with incorrect source, target, or transformation rules, leading to an illogical or unsupported path.
Missing Data Flow Components
Essential components of the data flow, such as connectors, mappings, or transformation routines, are either missing or not properly linked.
Insufficient User Permissions
The user or system account executing the data flow lacks the necessary authorizations to access specific data sources or targets.
Solutions
3 solutions available1. Verify and Recreate Data Flow Objects medium
This solution involves checking the integrity of data flow objects and recreating them if inconsistencies are found.
1
Identify the specific data flow object causing the error. This usually involves checking the context of the error message in SAP S/4HANA logs or tracing the execution path of the failed process.
2
Navigate to the relevant SAP S/4HANA transaction for data flow management. This might be in tools like SAP BW/4HANA modeling tools, SAP Analytics Cloud (SAC) data connection settings, or specific data integration tools used within your S/4HANA landscape.
3
Examine the configuration of the identified data flow. Look for any missing source or target objects, incorrect field mappings, or invalid transformation logic. Pay close attention to the connection details for data sources and targets.
4
If inconsistencies are found, delete the existing data flow object. Be cautious and ensure you have a backup or can easily recreate it.
5
Recreate the data flow object from scratch, ensuring all source and target connections are valid, field mappings are correct, and any transformation logic is properly defined. Test the recreated data flow thoroughly.
2. Check Underlying Data Source and Target Connectivity medium
Ensures that the data sources and targets used in the data flow are accessible and properly configured.
1
Determine the data sources and targets utilized by the problematic data flow. This information is typically available within the data flow's configuration in SAP S/4HANA or the associated data integration tool.
2
For each data source, verify its connectivity. If it's an SAP system, check RFC destinations (SM59) and user authorizations. If it's a non-SAP system or database, ensure network connectivity and credentials are correct.
3
For each target, confirm its accessibility and write permissions. This might involve checking database user privileges, file system permissions, or API endpoint availability.
4
If the data flow involves cloud services (e.g., SAP Data Intelligence, SAP Analytics Cloud connecting to S/4HANA OData services), verify the cloud connector configuration and the permissions granted to the service account.
5
Perform a test connection or a simple data read/write operation from the data integration tool to the source and target to validate connectivity and permissions independently of the data flow.
3. Review and Correct Metadata Definitions advanced
This solution focuses on ensuring that the metadata for data structures involved in the flow is accurate and synchronized.
1
Identify the specific tables, views, or data structures that are part of the data flow. This can be found by examining the data flow definition in your SAP S/4HANA modeling or integration tool.
2
Access the metadata definitions for these structures within SAP S/4HANA. For native S/4HANA tables, this can be done using transaction SE11. For virtual data models or CDS views, use relevant development tools.
3
Compare the metadata in the data flow configuration with the actual metadata in SAP S/4HANA. Look for discrepancies in table/view names, field names, data types, lengths, or primary/foreign key definitions.
4
If discrepancies are found, update the metadata in the data flow configuration to match the source system. If the source system metadata is incorrect, consider correcting it directly in SAP S/4HANA (e.g., by activating a corrected CDS view or adjusting a database table definition), but proceed with extreme caution and proper change management.
5
For CDS views, ensure they are active and correctly generated. You might need to re-generate or re-activate the CDS view after making any necessary corrections.