Why does governance so often slow everything down?
Because it is bolted on as policy instead of built in as engineering. Done properly, governance is what makes data — and the AI fed by it — trustworthy at speed: findable, understood, quality-assured and traceable end to end.
The questions we ask before anything is built
Governance earns its keep when it answers questions the business is already asking.
- Can anyone in your organisation find the data they need — and know whether to trust it?
- When a number is challenged in a board meeting, how long does it take to trace it to source?
- Which data feeds your AI — and who is accountable for its quality?
- What would a regulator, an auditor or a due-diligence team find tomorrow?
- Is your governance tooling serving the operating model, or substituting for one?
Capabilities, stated as outcomes
Catalogue implementation
Unity Catalog, Microsoft Purview and Collibra — implemented, migrated between, or exited from, with two decades of practitioner depth across all three.
Lineage & metadata
End-to-end lineage from source to dashboard to model — the traceability that turns 'we think' into 'we know'.
Data quality frameworks
Quality rules, monitoring and remediation workflows engineered into pipelines — not documented beside them.
Stewardship operating models
Roles, accountabilities and glossaries that fit how your organisation actually works — governance people follow because it helps them.
Three shapes of engagement
Governance engagements range from a focused catalogue implementation to designing the full operating model.
Advisory
Senior architecture counsel by the day — reviews, decision support, and a second pair of eyes on the choices that are hard to reverse.
Delivery
A small senior squad that designs and builds — architecture, engineering and knowledge transfer as one engagement, with confirmation gates at every phase.
Review & rescue
An independent, evidence-based assessment of an existing platform or stalled initiative, with a costed path forward.