Services
Mix & match modules depending on maturity and target state.
1) Data Governance
Build and evolve governance structures for regulatory requirements (incl. BCBS 239) as well as internal policies.
- Design of appropriate data architectures & target states
- Metadata modeling, glossary, ownership & RACI
- Control and evidence chains (lineage, data quality, reporting)
2) Data Architecture
Structured data landscapes that accelerate delivery — without later rework loops.
- Domain/product boundaries, interfaces & contracts
- Target architecture: Data Vault / warehouse / lakehouse
- Metadata & modeling standards
3) Data Quality & lineage
Measurability instead of gut feeling: rules, metrics and processes that can be operated sustainably.
- DQ rulebook, KPIs/thresholds, exception processes
- End-to-end lineage & impact analyses
- Automated checks in pipelines (DataOps)
4) Analytics & AI enablement
Clean data foundations, responsible usage and scalable operating models.
- Use-case selection, value tracking, governance
- Feature/metric definitions, data products
- Guardrails for models, monitoring & drift
5) Operating model & transformation
From roles and committees to concrete workflows — including adoption across the organization.
- Committees, decision paths, change & enablement
- Playbooks, templates, standards, trainings
- Roadmaps, pilots, scaling
6) Project support
Hands-on support in initiatives — as sparring partner or delivery role within workstreams.
- Requirements, concepts, reviews & quality assurance
- Stakeholder management, workshops, facilitation
- Deliverables: models, policies, architecture artifacts
How we work together
Transparent steps — quickly towards tangible outcomes.
1) Diagnose
Maturity, pain points, regulatory requirements and goals — condensed into a clear baseline.
2) Design
Target state, operating model, artifacts and prioritization — with pragmatic quick wins.
3) Delivery
Hands-on delivery, enablement and measurability — so it keeps working in operations.