SAP Master Data Governance
Enables governance, compliance and transparency of master data during creation and change through integrated staging, approval and central audit trail.
Delivers consistent definition, authorization and replication of key master data entities. Eliminates error prone manual maintenance processes for master data in multiple systems.
Consolidate master data in any enterprise system landscape, create best records and key mapping between duplicates, and optionally combine consolidation with central governance for sustained master data quality.
Provides native integration in SAP solutions, incl. re-use of data model, business logic, and configuration for validation while offering openness to integrate 3rd party services.
Open to extend the standard models and to create governance for your own master data and flexibly for non-SAP environments.
Measure Process quality using SAP Smart Business and integrate with SAP Data Services & SAP Information Steward for quality, enrichment, and data remediation.
SAP Data Services
SAP Data Services is a data integration and transformation software application. It allows users to develop and execute workflows that take data from predefined sources called data stores (applications, Web services, flat-files, databases, etc.) and then allows the user to combine, transform, and refine that data, and then output the results back to the same or different data stores.
- Discover, clean, improve and integrate data, and make them ready for use in the business.
- Ensure consistency between different data sources, whether on-premise, in the cloud or embedded in applications.
- Maximize the value of your data by allowing users to make confident decisions based on data they can trust.
- Improve processes and customer commitment by connecting customer, product, supplier, material and other data.
SAP Information Steward
Business users see how their information complies with business information quality standards and standards.
IT delivers quality metrics to business users and involves them in problem solving.
Understand and demonstrate how the wrong data affects the finances of your business.
Identify potential savings using what-if analysis of quality and cost levels.
Document the causes and metrics of the financial impact of each failed data.