One of the primary goals of any SAP implementation is to use the project momentum to cleanse the data and keep it clean. SAP facilitates consolidation of master data objects from decentralized legacy sources into a single platform — SAP itself, or tools like SAP MDM and MDG — building consistency and confidence in decision making while reducing regulatory and security risk.
This ETS overview explains why data quality is key to implementation success: completeness, validity, consistency, timeliness, and accuracy issues that multiply across business process networks spanning multiple companies, and how data governance acts as the quality-control mechanism for assessing, improving, monitoring, and protecting your core information.
It lays out the ETS six-step approach — Extract (identify sources and pull the building blocks of the new master data repository), Cleanse (deduplication, error elimination, column segmentation), Analyze (distill requirements into scope and match to available data), Transform (mapping, rules, coding, loading, output review), Migrate (test loads, validation, approval, production execution), and Govern (ongoing accuracy, completeness, and consistency).
The full overview is available above as a PDF and closes with the benefits of handling SAP data the right way: improved accuracy, reduced implementation risk, lower TCO through automation, better decisions, built-in compliance, and expert guidance throughout the transformation.