Data Architecture Consulting
Build a data foundation around the decisions that matter
Fragmented systems, duplicated data, and unclear ownership make every new report, integration, or analytics initiative harder to deliver. I help growing organizations define a data architecture that supports current priorities without creating unnecessary complexity. Data models, platforms, governance, and migration decisions stay connected to the business workflows they need to support.
When architecture becomes a delivery constraint
This service is designed for CTOs, Heads of Data, operations leaders, and technical teams that need to:
- consolidate conflicting data structures and duplicated sources;
- make a defensible platform, storage, or integration decision;
- clarify who owns critical data, quality rules, and access decisions;
- plan a migration without losing sight of existing operations;
- reduce architecture debt that slows reporting, analytics, or product delivery; or
- prepare a data foundation that can evolve as systems, teams, and requirements change.
If the immediate problem is a late or failing data flow, Data Engineering & Pipelines may be the clearer starting point. If the priority is consistent KPIs and management reporting, see Business Intelligence consulting.
What the engagement can deliver
The scope begins with the business priorities, existing landscape, constraints, and decisions that cannot wait. Depending on the situation, deliverables can include:
- a current-state assessment of data sources, storage, flows, dependencies, and risks;
- conceptual, logical, or physical data models that establish consistent structures and relationships;
- a target architecture with documented principles and decision rationale;
- an evaluation of database, warehouse, lake, or cloud platform options against actual requirements;
- an ownership and governance model covering standards, quality, access, privacy, and security;
- a prioritized migration or modernization roadmap; and
- implementation support, documentation, and handover for the internal team.
The objective is not the most elaborate architecture. It is a workable foundation that makes responsibilities and tradeoffs explicit, supports near-term delivery, and avoids preventable rework.
From current constraints to a practical target state
Work directly with Christian Stade-Schuldt from diagnosis through design and, where needed, implementation. This keeps business requirements, architecture decisions, and technical delivery connected.
- Clarify the priorities. Define the decisions, workflows, and initiatives the architecture must support.
- Assess the landscape. Review systems, data flows, models, ownership, quality issues, costs, and constraints.
- Design the target state. Compare realistic options and document the architecture, principles, and tradeoffs.
- Plan the transition. Sequence work around dependencies, risks, and the smallest useful increments.
- Support delivery and handover. Validate decisions through implementation where appropriate and transfer ownership with clear documentation.
Progress is measured against the original constraint. Relevant indicators can include duplicated data, access time, cloud cost, unresolved ownership, and the effort required to deliver a new data use case.
Plan your data foundation
Facing a platform decision, migration, or architecture bottleneck? Share the systems involved, the priority they need to support, and the constraint holding progress back. A focused architecture assessment or roadmap can provide a practical first step before a larger implementation is justified.