| Status | Approved |
|---|---|
| Owner | |
| Stakeholders |
Purpose
The purpose of this document is to define the conversion approach to create Batch Classes (Class Type: 023) in S/4 HANA.
Currently, in the legacy systems, batch classes are created and assigned to materials to capture logistics and quality-related information through characteristic values. However, there may be multiple duplicate classes existing within the system, which need to be standardized across both legacy systems as part of the SyWay Design.
Batch Class 023 in SAP is designed to store and manage characteristics relevant to batches, supporting both logistics and quality requirements for effective batch management and traceability.
Conversion Scope
The scope of this document covers the approach for converting active and valid Batch Classes from Legacy Source Systems (PF2 & WP2) into S/4HANA following the Batch Class (Class Type: 023) Master Data Design Standard.
Standardizing these Batch Classes ensures a consistent structure for batch data across materials and processes.
The data from legacy system includes:
- Batch Class of Class Type: 023
- Class Validity (Valid From and Valid To), Valid Date to be considered as Data of Extraction.
- Class Groups
- Characteristics Assignment
- Status as "1" - Released
The data from legacy system excludes:
- Status as "0" - In Preparation
- Status as "2" - Locked
- No Characteristics Assignment
| Source | Scope | Source Approx No. of Records | Target System | Target Approx No. of Records |
|---|---|---|---|---|
| PF2 | Only Valid Batch Class and with Characteristics Assignment | 1816 | SyWay - ERD | TBD |
| WP2 | Only Valid Batch Class and with Characteristics Assignment | 34 | SyWay - ERD | TBD |
Additional Information
Multi-language Requirement
Not Applicable
Document Management
Not Applicable
Legal Requirement
Not Applicable
Special Requirements
Target Design
The technical design of the target for this conversion approach.
| Table | Field | Data Element | Field Description | Data Type | Length | Requirement |
|---|---|---|---|---|---|---|
Data Cleansing
| ID | Criticality | Error Message/Report Description | Rule | Output | Source System |
|---|---|---|---|---|---|
Conversion Process
The high-level process is represented by the diagram below:
Data Privacy and Sensitivity
Extraction
Extract data from a source into . There are 2 possibilities:
- The data exists. connects to the source and loads the data into . There are 3 methods:
- Perform full data extraction from relevant tables in the source system(s).
- Perform extraction through the application layer.
- Only if ; cannot connect to the source, data is loaded to the repository from the provided source system extract/report.
- The data does not exist (or cannot be converted from its current state). The data is manually collected by the business directly in . This is to be conducted using DCT (Data Collection Template) in
The agreed Relevancy criteria is applied to the extracted records to identify the records that are applicable for the Target loads
Extraction Run Sheet
| Req # | Requirement Description | Team Responsible |
|---|---|---|
Selection Screen
| Selection Ref Screen | Parameter Name | Selection Type | Requirement | Value to be entered/set |
|---|---|---|---|---|
Data Collection Template (DCT)
Target Ready Data Collection Template will be created for data with exception of some fields which require transformation as mentioned in the transformation rule.DCT Rules
| Field Name | Field Description | Rule |
|---|---|---|
Extraction Dependencies
| Item # | Step Description | Team Responsible |
|---|---|---|
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 to make the data Target ready:
- Perform value mapping and data transformation rules.
- Legacy values are mapped to the to-be values (this could include a default value)
- Values are transformed according to the rules defined in
- 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
| Item # | Step Description | Team Responsible |
|---|---|---|
Transformation Rules
| Rule # | Source system | Source Table | Source Field | Source Description | Target System | Target Table | Target Field | Target Description | Transformation Logic |
|---|---|---|---|---|---|---|---|---|---|
Transformation Mapping
| Mapping Table Name | Mapping Table Description |
|---|---|
Transformation Dependencies
List the steps that need to occur before transformation can commence| Item # | Step Description | Team Responsible |
|---|---|---|
Pre-Load Validation
Project Team
Completeness
| Task | Action |
|---|---|
Accuracy
| Task | Action |
|---|---|
Business
Completeness
| Task | Action |
|---|---|
Accuracy
| Task | Action |
|---|---|
Load
The load process includes:
- Execute the automated data load into target system using load tool or product the load file if the load must be done manually
- Once the data is loaded to the target system, it will be extracted and prepared for Post Load Data Validation
Load Run Sheet
| Item # | Step Description | Team Responsible |
|---|---|---|
Load Phase and Dependencies
Configuration
| Item # | Configuration Item |
|---|---|
Conversion Objects
| Object # | Preceding Object Conversion Approach |
|---|---|
| list the exact title of the conversion object of only the immediate predecessor – this will then confirm the DDD (Data Dependency Diagram) | |
Error Handling
| Error Type | Error Description | Action Taken |
|---|---|---|
Post-Load Validation
Project Team
Completeness
| Task | Action |
|---|---|
Accuracy
| Task | Action |
|---|---|
Business
Completeness
| Task | Action |
|---|---|
Accuracy
| Task | Action |
|---|---|
Key Assumptions
- Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
- is in scope based on data design and any exception requested by business.