Privacy & Intelligence
Data Governance Strategy
Turn data from a liability into an asset. We build practical frameworks that improve quality, protect sensitive information, and enable trustworthy AI.
The Challenge: Data You Can't Trust
Conflicting reports, unclear "source of truth", and sensitive data spread across SharePoint, Teams, and file servers. With the Privacy Act reforms and the rise of Generative AI (Copilot), unmanaged data is now a critical business risk.
Good data governance isn't accidental—it's designed.
Our Practical Approach
Discover & Classify
We identify critical data assets (PII, Financials, IP). We map data flows and apply Sensitivity Labels using tools like Microsoft Purview.
Define Framework
We establish clear ownership (Data Stewards), define the "Source of Truth" for key metrics, and set lifecycle policies for retention and archival.
Implement & Empower
We roll out controls: DLP policies, access reviews, and cataloguing. We train your stewards so the model sustains after we leave.
Why Governance Matters Now
It's not just about compliance; it's about readiness.
- AI Readiness: You cannot deploy Copilot safely if your permissions are broken. Governance ensures AI only accesses what it should.
- Privacy Act: Know exactly what PII you hold, where it lives, and when to delete it.
- Trusted Decisions: Eliminate "report wars" by defining certified datasets for BI.
- ✓ Governance Framework (Roles & Responsibilities)
- ✓ Purview Configuration Plan (Labels & DLP)
- ✓ Data Lifecycle Policy (Retention/Deletion)
- ✓ 30/60/90 Day Roadmap