World's number one maker of flat glass and claims the top spot in automotive glass, plasma display panel substrates, and fluorinated resins. The company's electronics division makes high-purity silicon carbide, electronic components, and synthetic quartz glass for semiconductors and glass substrates, and its chemicals unit makes soda ash, caustic soda, and other specialty chemicals. It operates in more than 30 countries in Asia, Europe, and the Americas.
The customer planned to implement S/4 HANA, they wanted to understand the existing data from different ERP systems in order to perform the data consolidation and migration to S/4 HANA. They had 3 different ERP and Non-ERP applications running in different regions (Asia, Europe and North America). Some legacy applications (Non-SAP) are also part of the consolidation like JD Edwards and MAPICS. Business wanted to understand the data readiness for SAP S/4 HANA migration
A detailed data assessment was required to understand the 3 different ERP, Non-ERP applications data. Business wanted to identify the duplicate master records and potential data quality issues. Also, they wanted to know the inconsistent and incomplete master data. In order to check the data readiness for SAP S/4 HANA, it was necessary to do a prevalidation based on SAP S/4 HANA standard business rules and their current fields status group rules. Also, they are interested in knowing the open business documents and master data usage in downstream objects.
A detailed data assessment was performed and the results were shared with the business team for review.
Duplicate master records were identified and shared with the corresponding business team to review and eliminate the duplicate records.
As part of functional dependency check, all the open transactions and downstream objects were identified and reports and dashboards are shared with the business.
Prevalidation rules were built based on the S/4 HANA standard rules and current system business validations and all the source system data were validated to evaluate the quality.
dataZen and dataZap were used to perform the detailed data assessment steps.
Detailed data assessment helped a lot to understand the data even before starting the migration process, they were able to save plenty of time in the consolidation process.
Data Profiling provided a detailed view of their current data structure, interrelationships. Also, inconsistent and incomplete data was identified by the data profiling engine.
Functional dependency check provided all the Open transactions and downstream objects available for the master data.
Duplication check was performed, and the results were shared with the business. Duplicate master records were eliminated before migration based on business review and approval.
Data accuracy and readiness for SAP S/4 HANA was determined based on the pre validations results.
dataZap - Pre-Configured Templates & Migration Engine to Extract, Transform, Pre-Validate, Load, Reconcile & Report.
dataZen - To 'Get Clean' and 'Stay Clean', and Introduce Master Data Governance.