| Status | |
|---|---|
| Owner | |
| Stakeholders | CIRULE, Anita |
Purpose
The purpose of this document is to define the data conversion approach to create Customer Material Information Records (CMIR) in S/4 HANA.
Customer material info records (CMIRs) are used to store specific information about a material from a customer's perspective. This information helps in streamlining sales order processing and ensuring accurate order fulfilment. CMIRs link a customer's material number and description to the corresponding SAP material number, allowing for efficient order creation and data consistency.
This conversion aims to migrate active and relevant customer material information records from existing ECC systems into S/4HANA by applying required transformation logic using Syniti as the data migration and transformation platform. The converted records will be loaded into the target S/4HANA system using standard SAP mechanisms such as IDOCs, BAPIs, or direct table loads where applicable.
Conversion Scope
The scope of this document covers the approach for converting active Customer Material Information Records (CMIR) from Legacy Source Systems into S/4HANA following the Customer Material Information Records (CMIR) Master Data Design Standard: DD-FUN-050 Master Data Standard_1036-Customer Material Information Records(CMIR).
From the current system landscape, Customer Material Information Records (CMIR) exist in the both legacy systems - PF2 and WP2. Harmonization and validation are required to ensure the accurate and consolidated data in S/4HANA. While PF2 and WP2 serve as source systems, a mapping and transformation logic will be necessary to produce properly formatted load templates in line with the target design.
The data from legacy system includes:
All active Customer Material Information Records (CMIR), where:
- Customer sales view migrated as per CNV-3003 Business Partners - Customer (Sales and Service) - FLCU01
- AND Material sales view migrated as per CNV-2003 Materials - Sales view with sales long text.
- AND Sales organization is in scope of S/4HANA
- AND Distribution channel is in scope of S/4HANA
- OR Plant is in scope of S/4HANA (this is optional field; in ECC not all data have this maintained)
- For records selected in point #1 above; TEXT will be migrated if the Text ID and the language are included in the transformation mapping table.
| Source | Scope | Source Approx No. of Records | Target System | Target Approx No. of Records |
|---|---|---|---|---|
WP2 | Customer Material Info Records, table: KNMT | 26,000 | S/4HANA ROW | 26,000 |
PF2 | Customer Material Info Records, table: KNMT | 10,000 | S/4HANA ROW | 10,000 |
| WP2 | Customer Material Info Records, table: KNMT | 5,000 | S/4HANA China | 5,000 |
| PF2 | Customer Material Info Records, table: KNMT | 500 | S/4HANA China | 500 |
| WP2 | Customer Material Info Records, table: KNMT | 51,000 | S/4HANA CUI | 51,000 |
| PF2 | Customer Material Info Records, table: KNMT | N/A | S/4HANA CUI | N/A |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 0001 | 2,000 | S/4HANA ROW | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9010 | 4,000 | S/4HANA ROW | 4,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9011 | 10,000 | S/4HANA ROW | 10,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9012 | 8,000 | S/4HANA ROW | 8,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9013 | 6,000 | S/4HANA ROW | 6,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9016 | 2,000 | S/4HANA ROW | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9028 | 1,000 | S/4HANA ROW | 1,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9029 | 500 | S/4HANA ROW | 500 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9030 | 100 | S/4HANA ROW | 100 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9032 | 4,000 | S/4HANA ROW | 4,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9034 | 4,000 | S/4HANA ROW | 4,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9051 | 50 | S/4HANA ROW | 50 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9053 | 200 | S/4HANA ROW | 200 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9054 | 200 | S/4HANA ROW | 200 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9056 | 50 | S/4HANA ROW | 50 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9057 | 50 | S/4HANA ROW | 50 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z510 | 10 | S/4HANA ROW | 10 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z515 | 20 | S/4HANA ROW | 20 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z540 | 10 | S/4HANA ROW | 10 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z550 | 30 | S/4HANA ROW | 30 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z570 | 10 | S/4HANA ROW | 10 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z600 | 20 | S/4HANA ROW | 20 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z610 | 50 | S/4HANA ROW | 50 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z630 | 10 | S/4HANA ROW | 10 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z650 | 10 | S/4HANA ROW | 10 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z670 | 10 | S/4HANA ROW | 10 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z680 | 10 | S/4HANA ROW | 10 |
| PF2 | Customer Material Info Records, Text, table: STXH, text ID: Z950 | 50 | S/4HANA ROW | 50 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 0001 | 2,000 | S/4HANA China | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9010 | 10 | S/4HANA China | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9011 | 500 | S/4HANA China | 500 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9012 | 2,000 | S/4HANA China | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9013 | 2,000 | S/4HANA China | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9016 | 2,000 | S/4HANA China | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9028 | 500 | S/4HANA China | 500 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9029 | 50 | S/4HANA China | 50 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9030 | 10 | S/4HANA China | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9032 | 500 | S/4HANA China | 500 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9034 | 500 | S/4HANA China | 500 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 0001 | 50 | S/4HANA CUI | 50 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9010 | 500 | S/4HANA CUI | 500 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9011 | 3,000 | S/4HANA CUI | 3,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9012 | 2,000 | S/4HANA CUI | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9013 | 100 | S/4HANA CUI | 100 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9016 | 2,000 | S/4HANA CUI | 2,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9028 | 50 | S/4HANA CUI | 50 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9029 | 8,000 | S/4HANA CUI | 8,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9030 | 10 | S/4HANA CUI | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9032 | 1,000 | S/4HANA CUI | 1,000 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9034 | 500 | S/4HANA CUI | 500 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9051 | 10 | S/4HANA CUI | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9053 | 10 | S/4HANA CUI | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9054 | 10 | S/4HANA CUI | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9055 | 10 | S/4HANA CUI | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9056 | 10 | S/4HANA CUI | 10 |
| WP2 | Customer Material Info Records, Text, table: STXH, text ID: 9057 | 10 | S/4HANA CUI | 10 |
Additional Information
Multi-language Requirement
As per MDS, Text are only migrated for the valid/ approved language.
Document Management
N/A
Legal Requirement
N/A
Special Requirements
Due to compliance requirement, there will be one SAP instance for Rest of the World (ROW), one for China and one for CUI. Based on the sales organization the cross selling records will be migrated to respective SAP instances.
Target Design
Customer Material Information Records (CMIR) Data strictly adheres to the Master Data Standard. The complete information of the tables and key fields that hold the Customer Material Information Records (CMIR) information follows the Master Data Standard document.
The technical design of the target for this conversion approach.
| Table | Field | Data Element | Field Description | Data Type | Length | Requirement |
|---|---|---|---|---|---|---|
| KNMT | VKORG | VKORG | Sales Organization | CHAR | 4 | Mandatory |
| KNMT | VTWEG | VTWEG | Distribution Channel | CHAR | 2 | Mandatory |
| KNMT | KUNNR | KUNNR_V | Customer | CHAR | 10 | Mandatory |
| KNMT | MATNR | MATNR | Material | CHAR | 40 | Mandatory |
| KNMT | SORTL | SORTL | Search term | CHAR | 10 | Optional |
| KNMT | KDMAT | MATNR_KU | Customer Material | CHAR | 35 | Optional |
| KNMT | POSTX | KDPTX | Customer Description | CHAR | 40 | Optional |
| KNMT | LPRIO | LPRIO | Delivery Priority | NUMC | 2 | Optional |
| KNMT | MINLF | MINLF | Minimum Delivery Qty | QUAN | 13 | Optional |
| KNMT | KZTLF | KZTLF | Part.dlv./item | CHAR | 1 | Optional |
| KNMT | ANTLF | ANTLF | Max.Part.Deliveries | DEC | 1 | Optional |
| KNMT | UNTTO | UNTTO | Underdel. Tolerance | DEC | 3 | Optional |
| KNMT | UEBTO | UEBTO | Overdeliv. Tolerance | DEC | 3 | Optional |
| KNMT | UEBTK | UEBTK_V | Unlimited Tolerance | CHAR | 1 | Optional |
| KNMT | WERKS | WERKS_EXT | Plant | CHAR | 4 | Optional |
| KNMT | RDPRF | RDPRF | Rounding Profile | CHAR | 4 | Optional |
| KNMT | MEGRU | MEGRU | Unit of Measure Grp | CHAR | 4 | Optional |
| KNMT | VWPOS | VWPOS | Item Usage | CHAR | 4 | Optional |
| STXH | TDOBJECT | TDOBJECT | Texts: application object | CHAR | 10 | Optional |
| STXH | TDNAME | TDOBNAME | Name | CHAR | 70 | Optional |
| STXH | TDID | TDID | Text ID | CHAR | 4 | Optional |
| STXH | TDSPRAS | SPRAS | Language Key | LANG | 1 | Optional |
Data Cleansing
All data cleansing should take place in the data source system as defined in this document, unless system limitations prevent it.
| ID | Criticality | Error Message/Report Description | Rule | Output | Source System |
|---|---|---|---|---|---|
1036-001 | C1 | Customer with flag for deletion | Flag for deletion for all area (KNA1-LOEVM) OR flag for deletion at company code level (KNB1-LOEVM) OR flag for deletion at sales area level (KNVV-LOEVM) is 'X' - Yes | Source System/ Customer No./ Customer Name/ Country/ Company Code/ Company Code Name/ Sales Organization/ Sales Organization Name/ Distribution Channel/ Distribution Channel Name/ Division/ Division Name/ Flag for deletion for all area level/ Flag for deletion at company code level/ Flag for deletion at sales area level | PF2/ WP2 |
1036-002 | C1 | Customer with posting block | Posting block for all company code (KNA1-SPERR) OR posting block at company code level (KNB1-SPERR) is "X" - Yes | Source System/ Customer No./ Customer Name/ Country/ Company Code/ Company Code Name/ Posting block for all company code/ Posting block at company code level | PF2/ WP2 |
1036-003 | C1 | Customer with sales block | Sales block for all sales area (KNA1-CASSD) OR sales block at sales area level (KNVV-CASSD) is "X" - Yes | Source System/ Customer No./ Customer Name/ Country/ Sales Organization/ Sales Organization Name/ Distribution Channel/ Distribution Channel Name/ Division/ Division Name/ Sales block for all sales area/ Sales block at sales area level | PF2/ WP2 |
| 1036-004 | C1 | Customer with order block, delivery block or billing block | Order block for all sales area (KNA1-AUFSD) OR order block at sales area level (KNVV-AUFSD) OR delivery block for all sales area (KNA1-LIFSD) OR delivery block at sales area level (KNVV-LIFSD) OR billing block for all sales area (KNA1-FAKSD) OR billing block at sales area level (KNVV-FAKSD) is NOT BLANK. | Source System/ Customer No./ Customer Name/ Country/ Sales Organization/ Sales Organization Name/ Distribution Channel/ Distribution Channel Name/ Division/ Division Name/ Order block for all sales area (code + description)/ Order block at sales area level (code + description)/ Delivery block for all sales area (code + description)/ Delivery block at sales area level (code + description)/ Billing block for all sales area (code + description)/ Billing block at sales area level (code + description) | PF2/ WP2 |
| 1036-005 | C1 | Material with flag for deletion | Flag for deletion at client level (MARA-LVORM) OR flag for deletion at distribution chain level (MVKE-LVORM) is 'X' - Yes | Source System/ Material No./ Material Description/ Sales Organization/ Sales Organization Name/ Distribution Channel/ Distribution Channel Name/ Flag for deletion at client level/ Flag for deletion at distribution chain level | PF2/ WP2 |
| 1036-006 | C1 | Material with distribution-chain material status | Cross-distribution-chain material status (MARA-MSTAV) OR Distribution-chain-specific material status (MVKE-VMSTA) is NOT BLANK | Source System/ Material No./ Material Description/ Sales Organization/ Sales Organization Name/ Distribution Channel/ Distribution Channel Name/ Cross-distribution-chain material status code and the description/ Distribution-chain-specific material status code and the description | PF2/ WP2 |
| 1036-007 | C1 | PF2/ WP2 | |||
| 1036-009 | C1 | Syniti to provide Sales Report for the last 3 years for sales organization/ customer/ material with plant & ship-to country to determine the distribution channel | PF2/ WP2 |
Conversion Process
The high-level process is represented by the diagram below:
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
The process begins with extracting metadata and raw data from source systems, such as Syensqo ECC system (i.e., WP2/PF2) periodically. The extracted data is then staged for transformation.
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.
For CUI instance, the ETL process will be similar, but it will not use Syniti tool.
Data Privacy and Sensitivity
For SAP CUI instances, the data will be processed by US Based consultants.Extraction
Extract data from a source into Syniti Migrate for S/4HANA ROW and S/4HANA China relevant entities. There are 2 possibilities:
- The data exists. Syniti Migrate connects to the source and loads the data into Syniti Migrate. There are 3 methods:
- Perform full data extraction from relevant tables in the source system(s).
- Perform extraction through the application layer.
- Only if Syniti Migrate 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 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
For SAP CUI related entities, it will be alternative extraction process and the data will be stored in approved tools.
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 / US Based Consultant for SAP CUI instance Syniti / LTC Data team |
| 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 / US Based Consultant for SAP CUI instance |
| Extraction Execution Plan | - Establish execution timelines and batch processing schedules. - Assign responsibilities for extraction monitoring. - Document dependencies on other migration tasks. | Syniti / US Based Consultant for SAP CUI instance |
| Data Quality and Validation | - Define error handling mechanisms for extraction failures. | Syniti / US Based Consultant for SAP CUI instance |
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
| Field Name | Field Description | Rule |
|---|---|---|
Extraction Dependencies
List the steps that need to occur before extraction can commence
| Item # | Step Description | Team Responsible |
|---|---|---|
1 | Source System Availability
| Syensqo IT |
2 | Data Structure
| Syniti / US Based Consultant for SAP CUI instance |
3 | Referential Integrity
| Syniti / US Based Consultant for SAP CUI instance |
4 | Extraction Methodology
| Syniti / US Based Consultant for SAP CUI instance |
5 | Performance and Scalability Considerations
| Syniti / US Based Consultant for SAP CUI instance |
6 | Security and Compliance
| Syniti / US Based Consultant for SAP CUI instance |
7 | Data cleansing of legacy Customer Material Information Records (CMIR) data must be completed. If standardization within the DCT begins using relevant data from PF2 and WP2 before the cleansing is finalized, it is understood that the business will take due diligence to ensure any subsequent delta cleansing is verified and aligned within the DCT. | Business |
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.
- Legacy values are mapped to the to-be values (this could include a default value)
- 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
| Item # | Step Description | Team Responsible |
|---|---|---|
| 1 | Identify target S/4HANA fields and determine applicable legacy source fields from ECC system (PF2/ WP2). | Functional Team (L2C) + Data Team (L2C) |
| 2 | Map legacy field values to S/4HANA target values (including field-level mapping and technical names) | Data Team (L2C), Data Team (Syniti) |
| 3 | Define value mapping rules for fields requiring standardization or harmonization across the source systems | Functional Team (L2C) + Data Team (L2C) |
| 4 | Identify and agree on default values where legacy data is incomplete or inconsistent | Business Team + Functional Team (L2C) |
| 5 | Configure transformation rules in Syniti Migrate | Data Team (Syniti), Data Team (L2C) |
| 6 | Review transformation logic and mappings with Business for confirmation | Business Team + Functional Team (L2C) |
| 7 | Perform initial transformation run and generate draft target-ready dataset | Data Team (Syniti) |
| 8 | Review draft target-ready data for structure and completeness | Data Team (L2C), Functional Team (L2C) |
| 9 | Share transformed data with Business for Pre-load Validation | Business Team |
| 10 | Incorporate feedback from Business and refine mappings or transformation logic as needed | Data Team (L2C) |
| 11 | Finalize and approve transformed data as Target Ready Load File | Business + Functional (L2C) + Data Team (L2C) |
| 12 | Handover final file to Load Team or trigger the load via Syniti Load Workbench | Data Team (Syniti), Data Load Team |
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 |
|---|---|
MAP_VKORG | Sales Organization Mapping Table |
MAP_VTWEG | Distribution Channel Mapping Table Syniti to provide Sales Report for the last 3 years for sales organization/ customer/ material with plant & ship-to country to determine the distribution channel |
MAP_WERKS | Plant Mapping Table WERKS - Plant Share the same mapping table with S2P. To check with Jasleen Madhok, John Hancock, Angelo Buosi |
MAP_MATNR | Material Mapping Table |
MAP_KUNNR | Customer Mapping Table Covers mapping for ALL customers, incl.: KUNAG Sold-to KUNWE Ship-to |
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 / US Based Consultant for SAP CUI instance |
2 | Referential Integrity - Ensure dependent records are transformed together or in advance | Syniti / US Based Consultant for SAP CUI instance |
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 / US Based Consultant for SAP CUI instance |
5 | Logging and Error Handling - Maintain detailed logs of transformation activities. - Define error-handling procedures for failed transformations | Syniti / US Based Consultant for SAP CUI instance |
Pre-Load Validation
Project Team
The following pre-load validations will be performed by the Project Team.Completeness
| Task | Action |
|---|---|
Compare Data Counts |
|
Validate the mandatory fields | Validate there is value for all the mandatory fields |
Validate Primary Keys and Unique Constraints |
|
Test Referential Integrity | Confirm dependent records exist in related tables |
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 |
|
Business
The following pre-load validations will be performed by the business.Completeness
| Task | Action |
|---|---|
| Compare Data Counts |
|
| Review populated templates for missing or incorrect values | Use checklists to verify completeness and correctness before submission |
Accuracy
| Task | Action |
|---|---|
Conversion Accuracy | Business Data Owner/s to verify that all the data in the load table/file is accurate as per endorsed transformation/ mapping rules (and signed-off DCT data). |
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 | Confirm readiness of final approved data sets for each ECC source system WP2 and PF2 | Business / Functional Team |
| 2 | Validate transformation rules and mappings in Syniti tool | Data Team (L2C-Data) |
| 3 | Generate target-ready load files based on S/4HANA customer material info records table format | Data Team (Syniti) |
| 4 | Review and approve load files before execution | Business / Functional Team |
| 5 | Execute the upload program in the S/4HANA system | Data Load Team |
| 6 | Monitor load progress and capture load statistics (records loaded, errors, duplicates, etc.) | Data Team (Syniti) / Technical Team |
| 7 | Extract loaded data from S/4HANA for post-load validation | Data Team (Syniti) |
| 8 | Perform post-load data validation (compare target data with source/ approved files) for all loaded cross selling condition records | Data Team (L2C-Data) |
| 9 | Log and resolve any data load errors or mismatches identified during validation | Data Team (L2C-Data) + Functional Team |
| 10 | Obtain business sign-off on successful load and validation | Business Team |
| 11 | Archive load logs, error reports, and validation results for audit/compliance | Data Team (L2C-Data) / Data Team (Syniti) / PMO |
Load Phase and Dependencies
The Customer Material Information Records (CMIR) will be loaded in the pre-cutover period.
Before loading, it will have dependency on the configuration and data objects in the S/4 HANA. The configuration needs to be transported into the respective system first.
Configuration
List the Configurations required before loading can commence
| Item # | Configuration Item |
|---|---|
1 | Sales Organization |
2 | Distribution Channel |
3 | Plant |
| 4 | |
| 5 | |
| 6 | |
| 7 | |
| 8 | |
| 9 | |
10 |
Conversion Objects
| Object # | Preceding Object Conversion Approach |
|---|---|
3003 | Business Partners - Customer (Sales and Service) - FLCU01 |
2003 | Materials - Sales view with sales long text |
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 / Data Transformation | The value XXX for field XXX doesn't exist |
|
Configuration | There is mandatory field XXX missing |
|
Post-Load Validation
Project Team
The following post-load validations will be performed by the Project Team.Completeness
| Task | Action |
|---|---|
Validate Record count in the backend | Validate all tables has the same records as the loading file |
Display Records | Pick up a few random Customer and Material, and run t-code: VD53 to validate the Customer Material Information Records (CMIR) can be displayed without any error. |
Perform Source-to-Target Comparisons |
|
Accuracy
| Task | Action |
|---|---|
| Execute Sample Queries and Reports |
|
| Conduct Post-Migration Reconciliation | Generate reports comparing pre- and post-migration data. |
Business
Post-load validation is a critical step in data migration, ensuring that transferred data is accurate, complete, and functional within the target system.
1. Ensuring Data Integrity
After migration, data must be consistent with its original structure. Post-load validation checks for missing records, incorrect mappings, and formatting errors to prevent discrepancies.
2. Business Continuity
Faulty data can disrupt operations, leading to financial losses and inefficiencies. Validating post-load data ensures that applications function as expected, preventing downtime.
3. Error Detection and Resolution
By validating data post-migration, businesses can detect anomalies early, reducing the cost and effort required for corrections
Completeness
| Task | Action |
|---|---|
| Perform Source-to-Target Comparisons |
|
| Conduct Post-Migration Reconciliation | Go through reports comparing pre- and post-migration data. |
Accuracy
| Task | Action |
|---|---|
Perform Manual Testing | Conduct manual spot-checks for additional assurance. |
Key Assumptions
- Customer Material Information Records (CMIR) Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
- Customer Material Information Records (CMIR) is in scope based on data design and any exception requested by business.
- There will be 3 SAP instances, one for ROW, one for China and one for CUI only.
- For SAP CUI instance, the migration activity will be handled by US based data consultant.
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.