Status
Owner	RAYUDU-ext, Narasimha Kumar
Stakeholders	The business stakeholders involved in making, reviewing, and endorsing this decision. Type @ to mention people by name

Purpose

The purpose of this document is to define the conversion approach to create Batch Characteristics in S/4 HANA.

In both legacy systems, batch characteristics (class type 023) are used to hold key information related to Logistics & Quality information. Currently, there are more than 1,000 characteristics where these are duplicated with identical descriptions and assigned to different classes. To enable effective global utilization and reporting purposes, these characteristics need to be standardized. SyWay program to harmonize and standardize these characteristics across the organization.

Conversion Scope

The scope of this document covers the approach for converting active Batch Characteristics from Legacy Source Systems into S/4HANA following the Batch Characteristics Master Data Design Standard.

SAP Batch Characteristics are specific data fields used within the SAP system to describe and manage the properties of a batch of materials. They are part of the SAP Classification System and are typically associated with class type 023 (Batch Class).

Material Batches capture detailed information about each batch, such as production date, quality parameters, supplier details, or any other relevant property and enable traceability; allow track and trace batches throughout the supply chain with structured data for analysis and reporting.

The data from legacy system includes:

1. Characteristics assigned to Classes with below Class Type
• 023 – Batch Class (PF2, WP2)
2. Batch Characteristics assigned to Active Classes of 023.
3. Valid from [Current Date]
4. Status = 1 (Released)

The data from legacy system excludes:

1. Characteristics for Deletion (Deletion Indicator = X)

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
PF2	Batch Characteristics will be collected via DCT. An extract of the relevant Characteristics will be provided to assist business in standardizing the Characteristics from PF2 and WP2. If Any additional Characteristics that need to be created to support the new design may be added in the DCT.	4285
WP2	Batch Characteristics will be collected via DCT. An extract of the relevant Characteristics will be provided to assist business in standardizing the Characteristics from PF2 and WP2. If Any additional Characteristics that need to be created to support the new design may be added in the DCT.	1179

Additional Information

Multi-language Requirement

Characteristics descriptions are maintained in different languages.

Document Management

NA

Legal Requirement

NA

Special Requirements

NA

Target Design

With Functional input, document the technical design of the target fields that are in the scope of this document.

The technical design of the target for this conversion approach.

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
CABN	ATNAM	MATNR	Characteristic	CHAR	30	Mandatory
CABN	AENNR		Change Number	CHAR	12
CABN	DATUV		Valid From	DATS	8	Mandatory
CABNT	ATBEZ		Description	CHAR	40	Mandatory
CABN	ATKLA		Characteristic Group	CHAR	10
CABN	ATMST		Status	CHAR	1	Mandatory
CABN	ATAUTH		Authorisation Group	CHAR	3
CABN	ATFOR		Data Type	CHAR	4	Mandatory
CABN	ANZST		Number of Characters	INT2	5	Mandatory
CABN	ATKLE		Case Sensitive	CHAR	1
CABN	ATSCH		Template	CHAR	30
CABN	ANZDZ		Decimal places	INT2	5	Mandatory
CABN	CURRENCY		Currency			Mandatory (For Currency related Characteristics) / Optional
CABN	ATEIN		Value Assignment			Mandatory
CABN	MSEHI		Unit of Measure			Mandatory
CABN	ATDIM		Exponent Display			Mandatory
CABN	ATINT		Interval values allowed
CABN	ATVOR		Negative values allowed
CABN	ATGLA		Restrictable
CABN	ATERF		Entry Required
CABNT	SPRAS		Language			Mandatory
CABN	ATSON		Additional Values
CABN	ATTAB		Reference Table
CABN	ATFEL		Reference Field
CABN	DOKNR		Document
CABN	DOKAR		Document Type
CABN	DOKTL		Document Part
CABN	DOKVR		Document Version
CABN	ATINP		Not ready for input
CABN	ATVIE		No display
CABN	ATWRD		Display Allowed Values
CABN	ATFOD		Unformatted Entry
CABN	ATVSC		Propose Template

Data Cleansing

No data cleansing is required within the source systems. Standardization and cleansing activities will be carried out outside of the Syniti tool, and the finalized characteristics will be populated in the DCT.

ID	Criticality	Error Message/Report Description	Rule	Output	Source System
	NA	NA	NA	NA	NA

Conversion Process

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

Summarize High-Level Process. Include diagrams, where applicable. Include information supporting details of Extract, Transform and Load specific to the Data Object

Data Privacy and Sensitivity

Summarize Data Privacy and Sensitivity Requirements, if any

Extraction

Extract data from a source into Syniti Migrate. There are 2 possibilities:

1. The data exists. Syniti Migrate connects to the source and loads the data into Syniti Migrate. There are 3 methods:
   1. Perform full data extraction from relevant tables in the source system(s).
   2. Perform extraction through the application layer.
   3. Only if Syniti Migrate; cannot connect to the source, data is loaded to the repository from the provided source system extract/report.
2. The data does not exist (or cannot be converted from its current state). The data is manually collected by the business directly in Syniti Migrate. This is to be conducted using DCT (Data Collection Template) in Syniti Migrate

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

If applicable, this section will give the details on any selection screen parameters, including the parameter type, that are required to be entered to ensure consistent data extracts.

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 Object data with exception of some fields which require transformation as mentioned in the transformation rule.

<Object> DCT Rules

Field Name	Field Description	Rule

Extraction Dependencies

List the steps that need to occur before extraction can commence

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 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

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

Use the exact name and reference this section in the “Transformation rules” above

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

The following pre-load validations will be performed by the Project Team.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Business

The following pre-load validations will be performed by the business.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Load

The load process includes:

1. Execute the automated data load into target system using load tool or product the load file if the load must be done manually
2. 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

Identify the phase as to “when” the load for this object will occur. <Pre-Cutover, Cutover, Post Cutover> and list the steps that need to occur before the load can commence

Configuration

List the Configurations required before loading can commence

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

The table below depicts some possible system errors for this data object during data load. All data load error is to be logged as defect and managed within the Defect Management

Error Type	Error Description	Action Taken

Post-Load Validation

Project Team

The following post-load validations will be performed by the Project Team.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Business

The following post-load validations will be performed by the business.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Key Assumptions

• Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
• Data Object is in scope based on data design and any exception requested by business.

Any additional key assumptions.

See also

Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.

Change log