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09/06/2026 11:53 pm
TL;DR: Red Sea Global has become the first organisation in Saudi Arabia to go live with Collibra for NDMO and PDPL use cases, using catalog, lineage, and data quality controls to automate governance across sensitive guest data, according to Collibra. The broader lesson is that privacy and accountability now need embedded workflows, not manual review cycles.
NHIMG editorial — based on content published by Collibra: RSG's NDMO and PDPL governance deployment in Saudi Arabia
Questions worth separating out
Q: How should organisations operationalise NDMO and PDPL compliance at scale?
A: Organisations should treat NDMO and PDPL as workflow problems, not policy documents.
Q: Why do data lineage controls matter to IAM and governance teams?
A: Data lineage matters because accountability depends on reconstructing how sensitive information moved and changed hands.
Q: What breaks when privacy workflows stay manual in regulated environments?
A: Manual workflows create delay, inconsistency, and evidence gaps.
Practitioner guidance
- Embed classification into intake workflows Require new datasets, applications, and AI use cases to pass through classification and ownership assignment before they are consumed downstream.
- Use lineage as audit evidence Document end-to-end lineage for regulated datasets so auditors can see where data originated, where it moved, and which systems transformed it.
- Automate anomaly detection for governed data Monitor quality drift, unexpected joins, and unusual processing paths in sensitive datasets.
What's in the full analysis
Collibra's full article covers the operational detail this post intentionally leaves for the source:
- How RSG is applying Collibra Data Catalog, Data Lineage, and Data Quality & Observability in a live compliance environment
- The specific NDMO and PDPL workflows that are being operationalised across data teams and business units
- How the programme is positioned to extend into Collibra AI Governance for future AI use cases
- The vendor’s own description of how governance is being embedded into day-to-day operating processes
👉 Read Collibra's article on RSG's NDMO and PDPL governance deployment →
NDMO and PDPL compliance at scale: what does this change for IAM?
Explore further
10/06/2026 2:25 am
Operational privacy controls are becoming the new governance baseline. The article shows that regulatory compliance at scale is no longer sustained by policy plus periodic attestation. It now depends on embedded workflows that can classify, trace, and validate data handling as the business runs. For practitioners, that shifts governance from documentation to continuously provable control.
A few things that frame the scale:
- The average organisation believes more than 1 in 5 of their non-human identities are insufficiently secured, according to 2024 ESG Report: Managing Non-Human Identities.
- 72% of organisations have experienced or suspect they have experienced a breach of non-human identities, according to 2024 ESG Report: Managing Non-Human Identities.
A question worth separating out:
Q: How should security teams prepare for AI governance in regulated data programs?
A: Security teams should start by governing the data supply chain that feeds AI. That means defining ownership, access boundaries, lineage, and exception handling before models are expanded. If those foundations are weak, AI governance becomes a veneer over unmanaged data risk.
👉 Read our full editorial: Saudi data governance goes operational in NDMO and PDPL compliance
