Implementation guide
The Data Governance Guide
How to make data trusted, accessible and governed — the foundation AI and automation depend on.
What it is
AI and automation are only as good as the data beneath them. This guide covers establishing a trusted, governed, accessible data layer with consent and lineage built in.
Why it matters
Trusted data is the foundation every AI use case stands on.
Governance and consent protect you as data use scales.
Clear lineage means the numbers can be trusted and audited.
How to do it
1
Map the data
Catalogue sources, owners and sensitivity.
2
Establish a source of truth
Unify and reconcile key domains.
3
Govern access and consent
Scope, consent and audit it.
4
Make it real-time
Serve trusted data where systems act on it.
Readiness checklist
0 of 6 completeTools you’ll use
Data contracts
Versioned, governed exchange.
Governance checklist
Keeps it compliant.
Readiness assessment
Scores data readiness.
AI policy template
Sets data-use rules.
Risks to watch
Boil-the-ocean cataloguing
Start with the domains AI needs.
Consent gaps
Capture consent and scope access from the start.
Stale data
Monitor freshness and quality continuously.
What to measure
1
trusted source
100%
access role-scoped
Real-time
data where it acts
Run this guide with us.
Start from a readiness baseline and we’ll implement it with your team, tied to outcomes.