Status
Owner	REDDY-ext, Naren
Stakeholders

Purpose

The purpose of this document is to define the conversion approach to create 1151 Certificate Profiles in S/4 HANA.
in S/4 HANA.

Certificate Profiles are used in SAP Quality Management (QM) to control and define the certification requirements for materials and suppliers. A Certificate Profile specifies which quality certificates are required for a material, at what stage of the process they must be provided, and the specific inspection characteristics or parameters to be validated. This ensures that incoming materials or finished products meet the defined quality and regulatory standards before acceptance or shipment.

In SAP S/4HANA, the structure and usage of Certificate Profiles remain consistent with SAP ECC, generally defined by key attributes such as Material / Plant / Certificate Type. Certificate Profiles may include additional parameters such as certificate category, inspection lot linkage, and certificate relevance for procurement or production.

In SAP ECC, aside from the standard structure, Certificate Profiles may also exist with extended combinations or enhancements, for example:
    •    Profiles assigned to multiple materials or plants
    •    Custom fields defining regulatory or customer-specific certification needs
    •    Obsolete or inactive profiles that are no longer in use

Such cases must be reviewed carefully (MDS) to determine whether they remain relevant for migration.

This conversion aims to migrate active and valid Certificate Profiles from existing ECC systems into SAP S/4HANA by applying the required transformation logic using Syniti as the data migration and transformation platform. The converted records will be loaded into the target SAP S/4HANA system using standard SAP mechanisms such as BAPIs (e.g., BAPI_QM_CERTIFICATE_PROFILE_CREATE), IDOCs, or direct table loads, ensuring compliance with quality and regulatory requirements.

Conversion Scope

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

The data from legacy system includes:

1. All Active Certificate Profiles(Header table) active/created during the last 4 years
   QCVK-ERSTELDAT >= CURRENT DATE - 4

2. Certificate profile characteristics with Active MICs in the last 4 years. Refer Master Inspection characteristics.
   QCVM-MKMNR = QPMT-QPMT

3. Plant-specific Certificate Profiles that will be migrated to the To-Be Plant Mapping in Enterprise Structure Catalog worksheet "30. Plants"

4. Certificate Profiles referenced in active material-vendor (procurement).  Refer Material and BP-Vendor objects.

The data from legacy system excludes:

1. Certificate Profiles not used in more than four (4) years.

2. Certificate Profiles belonging to deleted plants (per To-Be Plant mapping).

3. Certificate Profiles referenced in inactive material-vendor (procurement).

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
PF2 & WP2	Certificate profiles data will be extracted from client PF2 and WP2	PF2 = 662 records WP2 =1709 records	S/4 HANA	2371

Additional Information

Multi-language Requirement

Not applicable

Document Management

Not applicable

Legal Requirement

Not applicable

Special Requirements

Not applicable

Target Design

The technical design of the target for this conversion approach.

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
QCVK	CTYP	QZGTYP	Certificate Type	CHAR	4	R
QCVK	VORLNR	QVORLNR	Certificate Profile Number	CHAR	12	R
QCVK	VERSION	QCVERSION	Version Number of Certificate Profile	CHAR	6	S
QCVK	SORTFELD	QSORTFELD	Search Field	CHAR	40	C
QCVK	GUELTIGAB	Q_UNUSEDDT	Field Not Used Field Reserved for SAP	DATS	8	S
QCVK	OBJNR	J_OBJNR	Object number	CHAR	22	S
QCVK	OBTYP	J_OBTYP	Object Category	CHAR	3	S
QCVK	STSMA	J_STSMA	Status Profile	CHAR	8	NU
QCVK	TDFORM	QCTDFORM	Form Name	CHAR	16	R
QCVK	KZGUTLOSE	QKZGUTLOSE	Indicator: Only Lots Whose Usage Decision is OK	CHAR	1	C
QCVK	MINQKZ	QKZMIN	Minimum Quality Score for Good Quality	DEC	3	C
QCVK	KZLASTLOT	QKZLASTLOT	Indicator: Last Lot for Batch	CHAR	1	C
QCVK	KZLIEFSCH	QKZLIEFSCH	Indicator: Delivery Note in Inspection Lot	CHAR	1	C
QCVK	HERKUNFT	QHERK	Inspection Lot Origin	CHAR	2	C
QCVK	ART	QPART	Inspection Type	CHAR	8	C
QCVK	KONSISTENT	QKZKONSIST	Indicator: Certificate Profile is Consistent	CHAR	1	NU
QCVK	KURZTEXT	QKURZTEXT	Short Text	CHAR	40	R
QCVK	LTEXTKZ	QKZLTX	Long Text Exists	CHAR	1	S
QCVK	WITHTRANSF	QCTRANSFER	Stock Transfers from Batch Where-Used List	CHAR	1	C
QCVK	QDI_NOPDF	QC_QDI_NOPDF	Indicator: Do Not Send PDF Document	CHAR	1	C
QCVK	ALSTF	QCALSTF	Expansion Level of Batch Where-Used List	NUMC	2	NU
QCVK	ADBFORM	QC_PDF_FORMNAME	PDF-Based Forms: Form Name	CHAR	30	NU
QCVK	QKZ_USEADB	QC_QKZ_USEADB	Use Adobe Form	CHAR	1	S
QCVK	CHAR_FIELD_CONF	QC_CHAR_FIELD_CONF	Configuration of Characteristics Field	CHAR	3	NU
QCVM	CTYP	QZGTYP	Certificate Type	CHAR	4	R
QCVM	VORLNR	QVORLNR	Certificate Profile Number	CHAR	12	R
QCVM	VERSION	QCVERSION	Version Number of Certificate Profile	CHAR	6	S
QCVM	BLOCKNR	QBLOCKNR	Number of Characteristic Block	NUMC	4	S
QCVM	MERKMALNR	QMKNR	Consecutive Characteristic Number	NUMC	4	S
QCVM	SORTNR	QSORTNR	Sort Number	NUMC	4	R
QCVM	TEXT_ELEM	QCTEXTELEM	Assignment of a Characteristic to a Form Text Element	CHAR	4	S
QCVM	KATEGORIE	QCCHARCAT	Characteristic Category for Certificates	CHAR	1	S
QCVM	ZAEHLER	WERKS_D	Plant	CHAR	4	R
QCVM	MKMNR	QMERKNR	Master Inspection Characteristics	CHAR	8	R
QCVM	VERSIONMK	QVERSNRMK	Version Number of the Master Inspection Characteristic	CHAR	6	C
QCVM	CMERKMALID	ATINN	Internal characteristic	NUMC	10	NU
QCVM	KZHERKWERT	QKZHERKWT	Origin of the Characteristic Result on the Certificate	CHAR	2	R
QCVM	KZHERKTEXT	QKZHERKTXT	Origin of Characteristic Short Text	CHAR	2	R
QCVM	KZAUSGFMT	QKZAUSGFMT	Characteristic Output Format	CHAR	2	C
QCVM	KZMETHODE	QKZMETHODE	Output Inspection Method	CHAR	2	C
QCVM	KZESEL	QKZESEL	Level for Result Selection	CHAR	1	R
QCVM	KZHERKVG	QKZHERKVG	Origin of Inspection Specifications	CHAR	2	R
QCVM	KZSTRSKIP	QKZSTRSKIP	Output Strategy for Skip Characteristics	CHAR	2	R
QCVM	MASSEINHSW	QMASSEH	Unit of Measurement, in Which Quantitative Data Is Stored	UNIT	3	S
QCVM	AUSGLEN	QLAENGE	Output Length	INT1	3	NU
QCVM	STELLEN	QSTELLEN	Number of Places to the Right of a Decimal Point (Accuracy)	INT1	3	C
QCVM	KZEXPDS	QKZEXPDS	Indicator: Exponential Notation	CHAR	1	NU
QCVM	KZOFFSPTX	QKZOFFSPTX	Additional Text When Result Is Outside Specifications	CHAR	1	NU
QCVM	KZOBL	QKZMKOBL	Indicator: Characteristic Required	CHAR	1	C
QCVM	VMSORTNR	QCSORTNR	Sort Number in List of Materials for Certificate Profile	NUMC	4	NU
QCVM	COLUMNSORT	QCCOLSORT	Display by Columns	CHAR	1	NU
QCVM	COLUMNS	QCCOLUMNS	Number of Columns	NUMC	2	NU
QCVM	UNITNRSORT	QCUNITSORT	Sort by Term for Inspected Unit	CHAR	1	NU
QCVM	CHARACT_ID1	QCHARACT_ID1	Characteristic Description for Quality Data Exchange	CHAR	40	C
QCVMT	CTYP	QZGTYP	Certificate Type	CHAR	4	R
QCVMT	VORLNR	QVORLNR	Certificate Profile Number	CHAR	12	R
QCVMT	VERSION	QCVERSION	Version Number of Certificate Profile	CHAR	6	S
QCVMT	BLOCKNR	QBLOCKNR	Number of Characteristic Block	NUMC	4	S
QCVMT	MERKMALNR	QMKNR	Consecutive Characteristic Number	NUMC	4	S
QCVMT	SPRACHE	SPRAS	Language Key	LANG	1	R
QCVMT	KURZTEXT	QKURZTEXT	Short Text	CHAR	40	R
QCVV	CTYP	QZGTYP	Certificate Type	CHAR	4	R
QCVV	VORLNR	QVORLNR	Certificate Profile Number	CHAR	12	R
QCVV	VERSION	QCVERSION	Version Number of Certificate Profile	CHAR	6	S
QCVV	VMKATEG	QCVMATKAT	Category of Data Origin (Insp. Lot/Batch) for Certificate	CHAR	1	R
QCVV	MATNR	MATNR	Material Number	CHAR	40	R
QCVV	COUNTER	QCVVCOUNT	Sequential Number for Material in a Certificate Profile	NUMC	3	S
QCVV	BLOCKNR	QBLOCKNR	Number of Characteristic Block	NUMC	4	S
QCVV	VMSORTNR	QCSORTNR	Sort Number in List of Materials for Certificate Profile	NUMC	4	S
QCVV	HERKUNFT	QHERK	Inspection Lot Origin	CHAR	2	C
QCVV	ART	QPART	Inspection Type	CHAR	8	C
QCVV	KZGUTLOSE	QKZGUTLOSE	Indicator: Only Lots Whose Usage Decision is OK	CHAR	1	C
QCVV	MINQKZ	QKZMIN	Minimum Quality Score for Good Quality	DEC	3	NU
KONDI	KNUMH	KNUMH	Cond.Record No.	CHAR	10	C
KONDI	CTYP	QZGTYP	CertificateType	CHAR	4	C
KONDI	VORLNR	QVORLNR	Cert. Profile	CHAR	12	C
KONDI	VERSION	QCVERSION	Version No.	CHAR	6	C
KONDI	ERSTELLER	QERSTELLER	Created By	CHAR	12	C
KONDI	ERSTELDAT	QDATUMERST	Created On	DATS	8	C
KOTI001	KAPPL	KAPPL	Application	CHAR	2	C
KOTI001	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI001	MATNR	MATNR	Material	CHAR	40	C
KOTI001	DATBI	KODATBI	Valid To	DATS	8	C
KOTI001	DATAB	KODATAB	Valid From	DATS	8	C
KOTI001	KNUMH	KNUMH	Cond.Record No.	CHAR	10	C
KOTI002	KAPPL	KAPPL	Application	CHAR	2	C
KOTI002	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI002	MATNR	MATNR	Material	CHAR	40	C
KOTI002	KNDNR	KUNNR_V	Customer	CHAR	10	C
KOTI002	DATBI	KODATBI	Valid To	DATS	8	C
KOTI002	DATAB	KODATAB	Valid From	DATS	8	C
KOTI002	KNUMH	KNUMH	Cond.Record No.	CHAR	10	C
KOTI501	KAPPL	KAPPL	Application	CHAR	2	C
KOTI501	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI501	WERKS	WERKS_D	Plant	CHAR	4	C
KOTI501	MATNR	MATNR	Material	CHAR	18	C
KOTI501	DATBI	KODATBI	Valid To	DATS	8	C
KOTI501	DATAB	KODATAB	Valid From	DATS	8	C
KOTI501	KNUMH	KNUMH	Cond.Record No.	CHAR	10	C
KOTI502	KAPPL	KAPPL	Application	CHAR	2	C
KOTI502	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI502	WERKS	WERKS_D	Plant	CHAR	4	C
KOTI502	MATNR	MATNR	Material	CHAR	18	C
KOTI502	KNDNR	KUNNR_V	Customer	CHAR	10	C
KOTI502	DATBI	KODATBI	Valid To	DATS	8	C
KOTI502	DATAB	KODATAB	Valid From	DATS	8	C
KOTI502	KNUMH	KNUMH	Cond.Record No.	CHAR	10	C
KOTI901	KAPPL	KAPPL	Application	CHAR	2	C
KOTI901	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI901	KUNWE	KUNWE	Ship-To Party	CHAR	10	C
KOTI901	MATNR	MATNR	Material	CHAR	18	C
KOTI901	DATBI	KODATBI	Valid to	DATS	8	C
KOTI901	DATAB	KODATAB	Valid From	DATS	8	C
KOTI901	KNUMH	KNUMH	Cond.record no.	CHAR	10	C
KOTI902	KAPPL	KAPPL	Application	CHAR	2	C
KOTI902	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI902	KUNWE	KUNWE	Ship-To Party	CHAR	10	C
KOTI902	MATKL	MATKL	Material Group	CHAR	9	C
KOTI902	DATBI	KODATBI	Valid to	DATS	8	C
KOTI902	DATAB	KODATAB	Valid From	DATS	8	C
KOTI902	KNUMH	KNUMH	Cond.record no.	CHAR	10	C
KOTI903	KAPPL	KAPPL	Application	CHAR	2	C
KOTI903	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI903	WERKS	WERKS_D	Plant	CHAR	4	C
KOTI903	KUNWE	KUNWE	Ship-To Party	CHAR	10	C
KOTI903	MATKL	MATKL	Material Group	CHAR	9	C
KOTI903	DATBI	KODATBI	Valid to	DATS	8	C
KOTI903	DATAB	KODATAB	Valid From	DATS	8	C
KOTI903	KNUMH	KNUMH	Cond.record no.	CHAR	10	C
KOTI904	KAPPL	KAPPL	Application	CHAR	2	C
KOTI904	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI904	WERKS	WERKS_D	Plant	CHAR	4	C
KOTI904	MATKL	MATKL	Material Group	CHAR	9	C
KOTI904	DATBI	KODATBI	Valid to	DATS	8	C
KOTI904	DATAB	KODATAB	Valid From	DATS	8	C
KOTI904	KNUMH	KNUMH	Cond.record no.	CHAR	10	C
KOTI905	KAPPL	KAPPL	Application	CHAR	2	C
KOTI905	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI905	VKORG	VKORG	Sales Org.	CHAR	4	C
KOTI905	MATKL	MATKL	Material Group	CHAR	9	C
KOTI905	DATBI	KODATBI	Valid to	DATS	8	C
KOTI905	DATAB	KODATAB	Valid From	DATS	8	C
KOTI905	KNUMH	KNUMH	Cond.record no.	CHAR	10	C
KOTI907	KAPPL	KAPPL	Application	CHAR	2	C
KOTI907	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI907	WERKS	WERKS_D	Plant	CHAR	4	C
KOTI907	KUNWE	KUNWE	Ship-To Party	CHAR	10	C
KOTI907	MATKL	MATKL	Material Group	CHAR	9	C
KOTI907	ZQ_OUTYPE	KSCHL	Condition type	CHAR	4	C
KOTI907	DATBI	KODATBI	Valid to	DATS	8	C
KOTI907	DATAB	KODATAB	Valid From	DATS	8	C
KOTI907	KNUMH	KNUMH	Cond.record no.	CHAR	10	C
KOTI908	KAPPL	KAPPL	Application	CHAR	2	C
KOTI908	KSCHL	KSCHI	Assignment type	CHAR	4	C
KOTI908	WERKS	WERKS_D	Plant	CHAR	4	C
KOTI908	MATKL	MATKL	Material Group	CHAR	9	C
KOTI908	ZQ_OUTYPE	KSCHL	Condition type	CHAR	4	C
KOTI908	DATBI	KODATBI	Valid to	DATS	8	C
KOTI908	DATAB	KODATAB	Valid From	DATS	8	C
KOTI908	KNUMH	KNUMH	Cond.record no.	CHAR	10	C

Data Cleansing

ID	Criticality	Error Message/Report Description	Rule	Output	Source System

Conversion Process

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

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 S/4HANA system. 

Data Privacy and Sensitivity

Not applicable

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
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 / 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
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 Screen	Parameter Name	Selection Type	Requirement	Value to be entered/set
Not applicable

Data Collection Template (DCT)

The Data Collection Template (DCT) will not be applicable in this case. If there is a need to create a new Master Data (MD) for Certificate Profiles object, the business must perform this activity in the source system. The newly created object will then be captured and migrated as part of the standard migration process.

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:

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
1	Transformation Scope Definition - Identify the source and target data structures. - Define business rules for data standardization. - Establish data cleansing requirements to remove inconsistencies.	Data Team
2	Data Mapping and Standardization - Align source fields with target fields. - Ensure unit consistency (e.g., currency, measurement units)	Data Team
3	Business Rule Application - Implement data enrichment/collection if applicable - Apply conditional transformations based on predefined logic/business rules	Data Team
4	Transformation Execution Plan - Define batch processing schedules. - Assign responsibilities for monitoring execution. - Establish error-handling mechanisms	Syniti

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

Completeness

Task	Action
Compare Data Counts	Verify row counts between source and target databases. Identify missing or duplicated records.
Validate the mandatory fields	Validate there is value for all the mandatory fields
Validate Primary Keys and Unique Constraints	Check for duplicate or missing primary key values. Ensure unique constraints are maintained.
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	Compare field values across systems Validate data formats and structures

Business

Completeness

Task	Action
Compare Data Count	Verify row counts between source and target databases. Identify missing or duplicated records.
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:

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 Scope Definition - Identify the target system and database structure. - Define data objects (tables, fields, records) to be loaded. - Establish business rules for data validation.	Data team
2	Load Methodology - Specify the loading tools and technologies (Migration Cockpit, LSMW, custom loading program).	Syniti
3	Data Quality and Validation - Ensure data integrity checks (null values, duplicates, format validation). - Perform pre-load validations to verify completeness. - Define error handling mechanisms for load failures	Syniti
4	Load Execution Plan - Establish execution timelines and batch processing schedules. - Assign responsibilities for monitoring execution. - Document dependencies on other migration tasks	Syniti
5	Logging and Reporting - Maintain detailed logs of loading activities. - Generate summary reports on loaded data volume and quality. - Define escalation procedures for errors	Syniti

Load Phase and Dependencies

The Certificate Profiles will be loaded in the pre-cutover (PreCutover 4 phase) period.

Before loading, it will have dependency on the following configuration and data objects in the S/4 HANA.

Configuration

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

Completeness

Task	Action
Validate Record count in the backend	Validate all tables with prefix “QINF” has the same records as the loading file
Display Records	Pick up a few random Material Listing or Material Exclusions, and run t-code: QI03 to validate the QIR and can be displayed without any error.
Perform Source-to-Target Comparisons	Validate that migrated data matches source records. Check for discrepancies in numerical values, text fields, and timestamps

Accuracy

Task	Action
Execute Sample Queries and Reports	Run queries to validate business logic. Generate reports to compare expected vs. actual results
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	Validate that migrated data matches source records. Check for discrepancies in numerical values, text fields, and timestamps
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

• Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
• Certificate Profiles is in scope based on data design and any exception requested by business.
• Data cleansing has met the required percentage threshold for the specified mock cycle and all preparation activities have been completed.
• Data entries in DCT are target-ready data unless a specific transformation rule is stated for that field in the transformation rules.

See also

Change log