Data Loss Prevention; DLP Microsoft Purview Specialist

Proof of Concept (POC) engagement to evaluate three leading data security and governance platforms — Microsoft Purview, Varonis, and BigID — across five core governance pillars:

• Data Classification & Labeling – Discover, classify, and label sensitive data across the enterprise.
• Access Transparency & Governance – Understand who has access to what data, identify excessive permissions, and establish data ownership.
• Policy-Driven Remediation – Automate enforcement, remediation workflows, and DLP controls.
• AI Data Risk Governance – Govern data exposure through AI tools including Copilot, ChatGPT, and enterprise AI apps.
• Continuous Governance & Reporting – Dashboards, compliance reporting, audit trails, and ongoing posture management.

Proof of Concept (POC) engagement to evaluate three leading data security and governance platforms — Microsoft Purview, Varonis, and BigID — across five core governance pillars:

The POC will be executed over a 12-week period and will produce a report on recommendations with comparative scoring and architecture guidance to support an informed platform selection decision along with additional 2 weeks for decommissioning of POC environment.

• Validate each platform s ability to discover, classify, and label sensitive data across Microsoft 365, on-premises file shares, Azure cloud, and SaaS applications.
• Assess access governance capabilities including permission analytics, data ownership identification, excessive access detection, and entitlement visibility.
• Evaluate policy-driven remediation workflows including automated enforcement, DLP integration, quarantining, and permission cleanup.
• Test AI data risk governance features include DSPM for AI, Copilot data governance, AI policy enforcement, and AI interaction monitoring.
• Measure reporting, dashboarding, and continuous governance capabilities including compliance posture, audit trails, and executive-level visibility.
• Produce a comprehensive report on recommendations including a scoring matrix, and architecture recommendation (single-vendor, best-of-breed, or phased hybrid approach).