Status
Owner	CASTRO MONCAYO-ext, Jose Luis
Stakeholders	GERVAIS, Pascal NICASTRI-ext, Michele

Purpose

The purpose of this document is to define the conversion approach to create <Data Object> in S/4 HANA.

Summarise how the data is currently utilized and set up in the legacy system/s and how object is intended to be represented in S/4, and any other relevant information

Conversion Scope

Material Master - PPDS Views are now used to make some of the Planning activities in both systems (PF2 & WP2). Most of the materials used in the planning process have these views updated, as they contain relevant information about the planning process. The aim is to get the conversion into S4 HANA in a standard way, so it can be used in the new planning processes already defined by the functional team and validated with the business.

While PF2 and WP2 serve as source systems, extensive mapping and transformation logic will be necessary to produce properly formatted load templates in line with the target design. As this is a new view a complete new DCT will be needed, as NO migration data on Scope.

We need to create a NEW Layout to fill in for the new data per material / Plant combination

The data from legacy system may include:

1. As per materials, the rule for this view will follow the rules for the CNV-2019 CNV-2019 Materials - Basic Data View 
   
   
2. Additional to this, the following criteria needs to be followed to create the view: All Direct materials as MRP type X0, will need to have PPDS view and the data to complete the design process in Syensqo.
3. All ZMAT materials and Z700 will be called in S4HANA ZDIR. These material types will be the ones to have PPDS View. 

The data from legacy system excludes:

1. All materials flagged for deletion
2. Any blocked or obsolete materials
3. Any inactive materials that are out of scope

The data from legacy system includes:

1. N/A
2. N/A

The data from legacy system excludes:

1. Exclusion Criteria 1
2. Exclusion Criteria 2
3. Exclusion Criteria n

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
PF2	All planning materials	15,000	S4 HANA	TBD
WP2	All Planning materials	30,000	S4 HANA	TBD
	N/A

Additional Information

Multi-language Requirement

System Multi-language standard definition

Document Management

N/A

Legal Requirement

N/A

Special Requirements

N/A

N/A

Target Design

Fields in Scope for PPDS view

The technical design of the target for this conversion approach.

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
MARA	MATNR	MATNR	Material Number	CHAR	18	R
T001W	WERKS	WERKS	Plant ID	CHAR	4	R
MARA	MEINS	MEINS	Unit of measure in which stock of the material is managed.	UNIT	3	R
MARA	PPSKZ	PPSKZ	Indicator for Advanced Planning	CHAR	1	C
MARC	SCM_PRIO	/SAPAPO/PRIO	Priority of Product	INT1	3	C
MARC	SCM_RRP_TYPE	/SAPAPO/PPS_PLANNING_TYPE	PP Planning Procedure	CHAR	1	C
MARC	SCM_RRP_SEL_GROUP	/SAPAPO/RRP_SEL_GROUP	Planning Group	CHAR	2	C
MARC	SCM_PEG_FUTURE_ALERT	/SAPAPO/DM_PEGGING_FUTUR_ALERT	Alert threshold for early receipts	DEC	11	C
MARC	SCM_PEG_PAST_ALERT	/SAPAPO/DM_PEGGING_PAST_ALERT	Alert Threshold for Lateness	DEC	11	C
MARC	SCM_GET_ALERTS	/SAPAPO/GET_ALERTS_FOR_PROD	Product Alerts	CHAR	1	C

Data Cleansing

No Data to clean as this is a new view in the Materials

If data cleansing is managed outside of the source system (e.g. Syniti Migrate, 3rd Party Vendor, DCT), the necessary documentation must be produced and appended to this deliverable for sign-off.

ID	Criticality	Error Message/Report Description	Rule	Output	Source System
		N/A

Conversion Process

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

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