Status
Owner	Prasad Naidu
Stakeholders	NG-ext, Bernard GARCIA-ext, Angel Luis PILLAY-ext, Lawrence

Purpose

The Business Partner role UKM000 is used to manage Credit Management data within the FSCM framework. With UKM000, credit data is maintained per credit segment (instead of credit control areas), ensuring accurate credit checks in sales and financial processes. Its purpose is to provide a unified, modern, and integrated way to control customer credit risk across the system.

Conversion Scope

The scope of this document covers the approach for converting active Customer Master Data from Legacy Source Systems into S/4HANA Business Partner Credit management UKM000 Master Data Design Standard.

The relevancy already applied in CNV3007. Once the customers in scope are finalized and extracted, we need to check the credit management fields for those customers in the legacy system and apply the transformation rules as per the source-to-target mappings.

List of source systems and approximate number of records

Source	Scope	Source Approx. No. of records	Target System	Target Approx. No. of records
PF2	Customer Master Data General Information	55371	S4	4200
WP2	Customer Master Data General Information	36983	S4	24000

Additional Information

Multi-language Requirement

NA

Document Management

Summarize Document Management requirement, if any

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
KNA1	KUNNR	KUNNR	Business Partner Number	CHAR	10	Required
UKMBP_CMS	CHECK_RULE	CHECK_RULE	Rule for Credit Check	CHAR	10	Required
UKMBP_CMS	RISK_CLASS	RISK_CLASS	Risk Class	CHAR	3	Required
UKMBP_CMS	CREDIT_GROUP	CREDIT_GROUP	Customer Credit Group	NUMC	4	Conditional
UKMBP_CMS_SGM	CREDIT_SGMNT	CREDIT_SGMNT	Credit Segment	CHAR	10	Conditional
UKMBP_CMS_SGM	CREDIT_LIMIT	CREDIT_LIMIT	Credit Limit	CURR	15, 2	Conditional
UKMBP_CMS_SGM	XBLOCKED	SGMXBLOCKED	Blocked	CHAR	1	Conditional
BUT100	RLTYP	BU_PARTNERROLE	BP Role	CHAR	6	Mandatory

Data Cleansing

This is not applicable for this Object

Conversion Process

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:

Extraction

Data will be extracted using Syniti ADMM from ECC

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.

Data Privacy and Sensitivity

N/A

Extraction

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

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.

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
Extraction Scope Definition	- Identify the source systems and databases involved. - Define the data objects (tables, fields, records) to be extracted. - Establish business rules for data selection.	Syniti Syniti
Extraction Methodology	- Specify the extraction approach (full, incremental, or delta extraction). - Determine the tools and technologies used. - Define data filtering criteria to exclude irrelevant records.	Syniti
Extraction Execution Plan	- Establish execution timelines and batch processing schedules. - Assign responsibilities for extraction monitoring. - Document dependencies on other migration tasks.	Syniti
Data Quality and Validation	- Define error handling mechanisms for extraction failures.	Syniti

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
N/A

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 - No DCT

Field Name	Field Description	Rule
N/A

Extraction Dependencies

List the steps that need to occur before extraction can commence

Item #	Step Description	Team Responsible
1	Source System Availability Ensure that the source database or application is accessible. Confirm that necessary credentials and permissions are granted	Syensqo IT
2	Data Structure Identify relationships between tables, views, and stored procedures.	Syniti
3	Referential Integrity Ensure dependent records are extracted together.	Syniti
4	Extraction Methodology Define whether extraction is full, incremental, or delta-based. Establish batch processing schedules for large datasets.	Syniti
5	Performance and Scalability Considerations Optimize extraction queries to prevent system overload. Ensure network bandwidth supports data transfer volumes.	Syniti
6	Security and Compliance Adhere to regulatory standards for sensitive information if applicable	Syniti

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:

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
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

NA

Transformation Rules

Rule #	Source system		Source Field	Source Description	Target System	Target Table	Target Field	Target Description	Transformation Logic
1	PF2/WP2	KNA1	KUNNR	Customer Number	S/4HANA	KNA1	KUNNR	Business Partner Number	Map from source to target using Business Partner mapping table
2	PF2/WP2	KNA1	KUNNR	Customer Number	S/4HANA	UKMBP_CMS	CHECK_RULE	Rule for Credit Check	Legacy to target Mappings will be provided by business
3	PF2/WP2	KNKK	CTLPC	Risk category	S/4HANA	UKMBP_CMS	RISK_CLASS	Risk Class	Legacy to target Mappings will be provided by business
4	PF2/WP2	KNKK	GRUPP	Customer Credit Group	S/4HANA	UKMBP_CMS	CREDIT_GROUP	Customer Credit Group	Legacy to target Mappings will be provided by business
5	PF2/WP2	KNKK	KKBER	Credit Control Area	S/4HANA	UKMBP_CMS_SGM	CREDIT_SGMNT	Credit Segment	Legacy to target Mappings will be provided by business
6	PF2/WP2	KNKK	KLIMK	Credit limit	S/4HANA	UKMBP_CMS_SGM	CREDIT_LIMIT	Credit Limit	Copy as-is
7	PF2/WP2	KNKK	CRBLB	Indicator: Blocked by credit management	S/4HANA	UKMBP_CMS_SGM	XBLOCKED	Blocked	Copy as-is
8	PF2/WP2	N/A	N/A	N/A	S4HANA	BUT100	RLTYP	BP Role	Default to UKM000

Transformation Mapping

Mapping Table Name	Description
Legacy Customer-BP Master Mapping	Legacy to S4 Business Partner customer mapping
Check Rule Mapping	Custom mapping for check rule based on the customer/BP number
Credit Segment Mapping	Custom mapping for credit segment based on the customer/BP number

Transformation Dependencies

List the steps that need to occur before transformation can commence

Item #	Step Description	Team Responsible
1	Source Data Integrity - Ensure extracted data is complete, accurate, and consistent. - Validate that data types and formats align with transformation requirements.	Syniti
2	Referential Integrity - Ensure dependent records are transformed together or in advance	Syniti
3	Transformation Logic and Mapping - Define data mapping rules between source and target schemas.	Data Team
4	Performance and Scalability Considerations - Optimize transformation processes for large datasets. - Ensure system resources can handle transformation workloads	Syniti
5	Logging and Error Handling - Maintain detailed logs of transformation activities. - Define error-handling procedures for failed transformations	Syniti

Pre-Load Validation

Project Team

Completeness

Task	Action
Verify count	Verify counts between source and target databases. Identify missing or duplicated records.
Validate the mandatory fields	Validate there is value for all the mandatory fields

Accuracy

Task	Action
Validate the transformation	Validate the fields which require transformation have the value after transformation instead of the original field value
Check Data Consistency	Compare field values across systems Validate data formats and structures

Business

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

Completeness

Task	Action
Verify Count for all customers	Verify that the record count in the pre-load file is the same as the record count based on the relevancy (including deduplication) results
Verify Relevancy Rules	Verify that the relevancy rules were correctly applied

Accuracy

Task	Action
Verify Data Accuracy	Verify that all the data in the load table/file is accurate as per signed-off transformation rules
Review Error Reports	Verify that all necessary error reports have been validated, and that errors have been addressed.
Verify Transformation Rules	Verify that the transformation rules are correct and have been carried out correctly

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
1	Load Sample Business Partners	Data
2	Validate sample Business Partners	Data
3	Load remaining Business Partners	Data
4	Validate data loaded for Business Partners	Data
5	Load Sample BP Type – Customer Contact Persons	Data
6	Validate sample BP Type – Customer Contact Persons	Data
7	Load remaining BP Type – Customer Contact Persons	Data
8	Validate data loaded for BP Type – Customer Contact Persons	Data
9	Load Sample BP Type – Vendor Contact Persons	Data
10	Validate sample BP Type – Vendor Contact Persons	Data
11	Load remaining BP Type – Vendor Contact Persons	Data
12	Validate data loaded for BP Type – Vendor Contact Persons	Data
13	Load Sample BP Type - Bank Contacts (First Name, Last Name)	Data
14	Validate sample BP Type - Bank Contacts (First Name, Last Name)	Data
15	Load remaining BP Type - Bank Contacts (First Name, Last Name)	Data
16	Validate data loaded for BP Type - Bank Contacts (First Name, Last Name)	Data
17	Load Sample BP Type – BP General, FI Customer, FI Vendor	Data
18	Validate sample BP Type – BP General, FI Customer, FI Vendor	Data
19	Load remaining BP Type – BP General, FI Customer, FI Vendor	Data
20	Validate data loaded for BP Type – BP General, FI Customer, FI Vendor	Data
21	Load Sample Vendors Default Partner	Data
22	Validate sample Vendors Default Partner	Data
23	Load remaining Vendors Default Partner	Data
24	Validate data loaded for Vendors Default Partner	Data
25	Load Sample BP - General for remaining customer roles	Data
26	Validate sample BP - General for remaining customer roles	Data
27	Load remaining BP - General for remaining customer roles	Data
28	Validate data loaded for BP - General for remaining customer roles	Data
29	Load Sample BP – Customers with Default Partner	Data
30	Validate sample BP – Customers with Default Partner	Data
31	Load remaining BP – Customers with Default Partner	Data
32	Validate data loaded BP – Customers with Default Partner	Data
33	Load Sample BP - Bank Role	Data
34	Validate sample BP - Bank Role	Data
35	Load remaining BP - Bank Role	Data
36	Validate data loaded BP - Bank Role	Data
37	Load Sample BP Relationship Contact Person to Organisation (Will create KNVK records)	Data
38	Validate sample BP Relationship Contact Person to Organisation (Will create KNVK records)	Data
39	Load remaining BP Relationship Contact Person to Organisation (Will create KNVK records)	Data
40	Validate data loaded for BP Relationship Contact Person to Organisation (Will create KNVK records)	Data
41	Load Sample BP - Carrier	Data
42	Validate sample BP - Carrier	Data
43	Load remaining BP - Carrier	Data
44	Validate data loaded BP - Carrier	Data
45	Load Sample BP - Credit Management	Data
46	Validate sample BP - Credit Management	Data
47	Load remaining BP - Credit Management	Data
48	Validate data loaded BP - Credit Management	Data
49	Load Sample BP Collections Management	Data
50	Validate sample BP Collections Management	Data
51	Load remaining BP Collections Management	Data
52	Validate data loaded BP Collections Management	Data

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
1	Obtain the approved upload USER ID’s to be used (e.g. Firefighter ID)
2	SAP USER profile (SU3) Date and Decimal Notation Formats are in sync with the load format
3	Company Code Configuration
4	BP Grouping
5	Customer Account Group
6	BP Number Range

Conversion Objects

Object #	Preceding Object Conversion Approach
N/A

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

Configuration

<configuration> is not valid/missing

If it is a missing configuration item then engage Functional team to expedite and fix the error in the system.

Invalid Data

<parameter> is not valid.

The parameter entry needs to be reviewed (ex. invalid payment terms).

If it is an invalid data, business needs to review and correct the source of the data either in PF2/PI2/WP2

Technical Setup

Interface / Connection issue within target system’s landscape

N/A – the data will be loaded directly to S/4HANA environment

Post-Load Validation

Project Team

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

Completeness

Task	Action
Perform Data Count	Validate that migrated data matches source records.
Perform Source-to-Target Comparisons	Validate all the mandatory fields are populated as per the loading file

Accuracy

Task	Action
Data Accuracy	Data team to verify that all the data in the load table/file is accurate as per signed-off transformation rules
Error Reports	Verify that all necessary error reports have been validated, and that errors have been addressed.

Business

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

Completeness

Task	Action
Perform Source-to-Target Comparisons	Validate that migrated data matches source records counts.
Conduct Post-Migration Reconciliation	Go through reports comparing pre- and post-migration data provided by Syniti.

Accuracy

Task	Action
Verify Data Accuracy	Data team to verify that all the data in the load table/file is accurate as per signed-off transformation rules
Review Error Reports	Verify that all necessary error reports have been validated, and that errors have been addressed.
Validate Loaded Data	Validate, as per the loads files signed-off, that all records were created

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.

Purpose

Conversion Scope

Additional Information

Multi-language Requirement

Document Management

Legal Requirement

Special Requirements

Target Design

Data Cleansing

Conversion Process

Data Privacy and Sensitivity

Extraction

Extraction Run Sheet

Selection Screen

Data Collection Template (DCT)

Extraction Dependencies

Transformation

Transformation Run Sheet

Transformation Mapping

Transformation Dependencies

Pre-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Load

Load Run Sheet

Configuration

Conversion Objects

Error Handling

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Key Assumptions

See also

Change log

Workflow history