Purpose

The purpose of this document is to define the conversion approach to migrate Attachment for customer master data in S/4 HANA.

Attachments in SAP ECC are typically stored using Generic Object Services (GOS), which allow users to link files to master data objects such as customers (via transaction codes like XD02). Attachments in SAP S/4HANA are linked using the Attachment List Service (also used in Fiori apps). This conversion specification will capture the details on how to migrate the attachments for those customers in migration scope into S4 Hana to keep the business continuity.

Conversion Scope

The scope of this document covers the approach for converting Attachment for active Customer master data from SAP ECC into S/4HANA following the document "DD-FUN-050 Master Data Standard_3004-Attachment for customer master data". 

The data from legacy system includes:

1. The customer general data is in migration scope. (Scope is elaborated in CNV-3007 Business Partners - General (Role 000000) )
2. There is attachment maintained in legacy ECC system (WP2/PF2) for the active customers. The attachment relationship type includes note, private note, attachment. 

The data from legacy system excludes:

1. Attachment for customer outside of migration scope.
2. Non-SAP ECC (WP2/PF2) attachment

Additional Information

Multi-language Requirement

N/A

Document Management

The DMS approach is elaborated in KDD "KDD085 - Document Management in the SyWay Solution". The migration approach for the attachment will follow the DMS approach approved in this KDD.

Legal Requirement

CMMC 2.0 is a mandatory DoD cybersecurity certification for contractors handling Controlled Unclassified Information (CUI) and Federal Contract Information (FCI). CUI includes sensitive technical data (e.g., design specs, system info) related to U.S. military and space applications. The Composites Business handles CUI and is therefore within CMMC scope. Without certification, the business risks disqualification from existing and future DoD programs.
It is mandatory to implement CMMC-compliant systems and processes to for all the organizations that are dealing with CUI.

For this data object, if there is CUI related information, it will be handled by the US based consultants to meet the compliance requirement.

Special Requirements

N/A

Target Design

The technical design of the target for this conversion approach.

Data Cleansing

Conversion Process

The high-level process is represented by the diagram below:

The ETL (Extract, Transform, Load) process is a structured approach to data migration and management, ensuring high-quality data is seamlessly transferred across systems. Here’s a breakdown of its key components:

1. Extraction
The process begins with extracting metadata and raw data from source systems, such as Syensqo ECC system (i.e., WP2/PF2) periodically. The extracted data is then staged for transformation.

2. Transformation
Once extracted, the data undergoes cleansing, consolidation, and governance. This step ensures data integrity, consistency, and compliance with business rules. The transformation process includes:
- Data validation to remove inconsistencies.
- Standardization to align formats across datasets.
- Business rule application to refine data for operational use.

3. Loading
The transformed data is then loaded into the target S4 Hana system. For attachment, it will be migrated via a custom program. The table list down the major steps to perform this ETL process.

Data Privacy and Sensitivity

N/A

Extraction

Extract data from SAP ECC table SRGBTBREL into Syniti Migrate. The data exists. Syniti Migrate connects to the source and loads the data into Syniti Migrate. Then perform full data extraction from relevant tables in the source system(s).

Extraction Run Sheet

Sample template to download the attachment from SAP

Selection Screen

Data Collection Template (DCT)

DCT Rules

Extraction Dependencies

Transformation

The Target fields are mapped to the applicable Legacy field that will be its source, this is a 3-way activity involving the Business, Functional team and Data team. This identifies the transformation activity required to allow Syniti Migrate to make the data Target ready:

1. Perform value mapping and data transformation rules.
   1. Legacy values are mapped to the to-be values (this could include a default value)
   2. Values are transformed according to the rules defined in Syniti Migrate
2. Prepare target-ready data in the structure and format that is required for loading via prescribed Load Tool. This step also produces the load data ready for business to perform Pre-load Data Validation

Transformation Run Sheet

Transformation Rules

Transformation Mapping

Transformation Dependencies

Pre-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Load

The load process includes:

1. Execute the data load into target system using load tool 
2. Once the data is loaded to the target system, it will be extracted and prepared for Post Load Data Validation

Load Run Sheet

This object will be loaded via a custom program. The custom program will use the upload template below. 

Load Phase and Dependencies

The Attachment for customer master data will be loaded in the pre-cutover period.

Before loading, it will have dependency on the DMS server set up. 

Configuration

Conversion Objects

Error Handling

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Post-load validation is a critical step in data migration, ensuring that transferred data is accurate, complete, and functional within the target system.

1. Ensuring Data Integrity
After migration, data must be consistent with its original structure. Post-load validation checks for missing records, incorrect mappings, and formatting errors to prevent discrepancies.
2. Business Continuity
Faulty data can disrupt operations, leading to financial losses and inefficiencies. Validating post-load data ensures that applications function as expected, preventing downtime.
3. Error Detection and Resolution
By validating data post-migration, businesses can detect anomalies early, reducing the cost and effort required for corrections

Completeness

Accuracy

Key Assumptions

• Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
• Attachment for customer master data is in scope based on data design and any exception requested by business.
• There will be 3 SAP instances, one for ROW, one for China and one for CUI only.

See also

Change log

Workflow history