Across everything
A target architecture your team can deliver.
We design data, AI and integration architectures and a data strategy with clear priorities — from current state to roadmap, aligned with IT, business teams and SAP.
Typical situations
- Many initiatives, but no shared target picture for data, AI and SAP.
- Technology decisions are due: Databricks, Microsoft Fabric, SAP Datasphere or Business Data Cloud?
- Governance, roles and ownership of data are unclear.
- Projects start without operations, cost and security being planned in.
- Data and AI budgets are allocated per project, without visible prioritization by value.
- The system landscape has grown over the years: many interfaces, duplicate data, unclear systems of record.
- Business teams and IT have different ideas of what a data platform should deliver.
- A cloud or SAP migration is coming up, and the data architecture should be designed along with it.
What we deliver
- Current-state analysis of system landscape, data flows and processes
- Target architecture for data, AI and integration (e.g., lakehouse, hub and spoke, SAP connectivity)
- Data strategy with policies, governance and roles (data ownership)
- Technology assessment and selection, with a transparent rationale
- Prioritized roadmap with effort, value and risks
- Architecture guidance during delivery: reviews and decision papers
- Architecture decisions documented (ADR, arc42) so they stay traceable
- Cost and operating model for the target platform: FinOps, roles, support
Technologies
- TOGAF
- UML
- Medallion-Architektur
- Hub & Spoke
- Unity Catalog
- SAP Business Data Cloud
- Microsoft Fabric
Outcome
An agreed target architecture and a roadmap your team and your partners can deliver against.