01Data landscape and roadmap
Map source systems, business definitions, existing warehouse investments and consumption needs. Establish the role of Datasphere relative to BW/4HANA, SAC and other enterprise platforms before selecting a migration or integration approach.
02SAP and non-SAP integration
Evaluate supported connections and data movement patterns. Design ingestion, replication or federation where appropriate, documenting freshness, reconciliation, source impact and the operational responsibilities for each data flow.
03Business and semantic modeling
Design reusable analytical models, relationships and business definitions. Separate source complexity from consumption needs so teams can build consistent analytics without redefining measures independently across every report.
04Security and governance
Define spaces, roles, data access and ownership responsibilities around your operating model. Establish conventions for development, controlled deployment, stewardship and review so that governed access remains manageable as adoption grows.
05BW coexistence and modernization
Evaluate existing BW assets and dependencies. Assess reuse and transition options, including relevant BW bridge scenarios, against compatibility, licensing, functional fit and the effort required to preserve established business logic.
06SAC enablement and operations
Connect agreed data models to SAC consumption patterns. Validate results and performance, document dependencies and establish monitoring, issue handling and change control for the data services supporting business-critical analytics.