Status

100%

OwnerPrasad Naidu
Stakeholders

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 

SourceScopeSource Approx. No. of recordsTarget SystemTarget Approx. No. of records
PF2Customer Master Data General Information55371S44200
WP2Customer Master Data General Information36983S424000


Additional Information

Multi-language Requirement

NA

Document Management

Legal Requirement

NA

Special Requirements

NA




Target Design

The technical design of the target for this conversion approach.

TableFieldData ElementField DescriptionData TypeLengthRequirement
KNA1KUNNRKUNNRBusiness Partner NumberCHAR10Required
UKMBP_CMSCHECK_RULECHECK_RULERule for Credit CheckCHAR10Required
UKMBP_CMSRISK_CLASSRISK_CLASSRisk ClassCHAR3Required
UKMBP_CMSCREDIT_GROUPCREDIT_GROUPCustomer Credit GroupNUMC4Conditional
UKMBP_CMS_SGMCREDIT_SGMNTCREDIT_SGMNTCredit SegmentCHAR10Conditional
UKMBP_CMS_SGMCREDIT_LIMITCREDIT_LIMITCredit LimitCURR15, 2Conditional
UKMBP_CMS_SGMXBLOCKEDSGMXBLOCKEDBlockedCHAR1Conditional
BUT100RLTYPBU_PARTNERROLE

BP Role

CHAR6Mandatory


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:

  1. 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 . There are 2 possibilities:

  1. The data exists. connects to the source and loads the data into . 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 ; 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

Selection Ref ScreenParameter NameSelection TypeRequirementValue to be entered/set
N/A



















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   - No DCT

Field NameField DescriptionRule
N/A










Extraction Dependencies

Item #Step DescriptionTeam 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 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
  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

NA

Transformation Rules

Rule #Source system
Source FieldSource DescriptionTarget SystemTarget TableTarget FieldTarget DescriptionTransformation Logic
1PF2/WP2KNA1KUNNRCustomer NumberS/4HANAKNA1KUNNRBusiness Partner NumberMap from source to target using Business Partner mapping table
2PF2/WP2KNA1KUNNRCustomer NumberS/4HANAUKMBP_CMSCHECK_RULERule for Credit CheckLegacy to target Mappings will be provided by business
3PF2/WP2KNKKCTLPCRisk categoryS/4HANAUKMBP_CMSRISK_CLASSRisk ClassLegacy to target Mappings will be provided by business
4PF2/WP2KNKKGRUPPCustomer Credit GroupS/4HANAUKMBP_CMSCREDIT_GROUPCustomer Credit GroupLegacy to target Mappings will be provided by business
5PF2/WP2KNKKKKBERCredit Control AreaS/4HANAUKMBP_CMS_SGMCREDIT_SGMNTCredit SegmentLegacy to target Mappings will be provided by business
6PF2/WP2KNKKKLIMKCredit limitS/4HANAUKMBP_CMS_SGMCREDIT_LIMITCredit Limit Copy as-is
7PF2/WP2KNKKCRBLBIndicator: Blocked
 by credit management 
S/4HANAUKMBP_CMS_SGMXBLOCKEDBlockedCopy as-is
8PF2/WP2

N/A

N/A

N/A

S4HANA

BUT100RLTYP

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


Pre-Load Validation

Project Team

Completeness

TaskAction

Verify count

  1. Verify counts between source and target databases.
  2. Identify missing or duplicated records.
Validate the mandatory fieldsValidate there is value for all the mandatory fields

Accuracy

TaskAction
Validate the transformationValidate the fields which require transformation have the value after transformation instead of the original field value
Check Data Consistency
  1. Compare field values across systems
  2. Validate data formats and structures

Business

Completeness

TaskAction

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

TaskAction

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:

  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

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

Configuration

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

4BP Grouping
5Customer Account Group
6BP Number Range

Conversion Objects

Object #Preceding Object Conversion Approach

N/A








Error Handling

Error TypeError DescriptionAction 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

Completeness

TaskAction
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

TaskAction

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

Completeness

TaskAction
Perform Source-to-Target Comparisons

Validate that migrated data matches source records counts.

Conduct Post-Migration ReconciliationGo through reports comparing pre- and post-migration data provided by Syniti.

Accuracy

TaskAction

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.
  • is in scope based on data design and any exception requested by business.


See also

Change log

Version Published Changed By Comment
CURRENT (v. 34) Apr 22, 2026 15:59 NAIDU-ext, Prasad
v. 33 Apr 22, 2026 13:43 NAIDU-ext, Prasad
v. 32 Mar 13, 2026 11:55 NAIDU-ext, Prasad
v. 31 Mar 13, 2026 11:13 NAIDU-ext, Prasad
v. 30 Nov 20, 2025 12:28 PILLAY-ext, Lawrence
v. 29 Nov 20, 2025 12:24 PILLAY-ext, Lawrence
v. 28 Nov 19, 2025 16:29 NAIDU-ext, Prasad
v. 27 Nov 18, 2025 15:38 NAIDU-ext, Prasad
v. 26 Nov 18, 2025 10:53 NAIDU-ext, Prasad
v. 25 Nov 17, 2025 11:06 NAIDU-ext, Prasad

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