<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Saudi-Data-Governance on SAUDI VISION 2030 Intelligence Platform</title><link>https://vision2030.ai/clusters/saudi-data-governance/</link><description>Recent content in Saudi-Data-Governance on SAUDI VISION 2030 Intelligence Platform</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 26 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://vision2030.ai/clusters/saudi-data-governance/feed.xml" rel="self" type="application/rss+xml"/><item><title>NDMO compliance operating map: classification, sharing, privacy, and AI data controls</title><link>https://vision2030.ai/analysis/ndmo-data-governance-policies-classification-sharing-privacy-compliance/</link><pubDate>Tue, 26 May 2026 00:00:00 +0000</pubDate><guid>https://vision2030.ai/analysis/ndmo-data-governance-policies-classification-sharing-privacy-compliance/</guid><description>&lt;p>NDMO data governance policies are Saudi Arabia&amp;rsquo;s operating baseline for public-sector data classification, sharing, open data, privacy, quality, security, and compliance evidence. They matter because AI systems, digital-government services, open-data portals, cloud workloads, and cross-agency analytics depend on governed data before models or dashboards can be trusted. The practical question is not whether an organization has a data governance framework ppt. It is whether it can prove ownership, classification, metadata, quality, sharing authority, privacy basis, retention, and access controls before data is moved, published, monetized, or used in automated decision support. Read this as a governance briefing, not legal advice. [S1] [S2]&lt;/p></description></item></channel></rss>