1. Understand the Purview Security and Governance System
Map the Purview Landscape and Its Security Boundaries Translate Licensing, Roles, and Governance into an Operating Model
2. Discover, Map, and Curate the Data Estate
Design Data Map Scanning and Metadata Collection Build Unified Catalog, Lineage, Quality, and Data Products
3. Classify and Protect Information
Engineer Sensitive Information Types and Classifiers Design Sensitivity Labels, Publishing, and Auto-Labeling
4. Prevent Unsafe Data Movement
Design DLP Policies from Business Scenarios Extend DLP to Endpoints, Browsers, Teams, and AI
5. Govern the Information Lifecycle
Design Retention Policies and Labels Operate Records, Events, Disposition, and Legal Holds
6. Investigate and Preserve Evidence
Use Purview Audit as Evidence Run eDiscovery Cases, Holds, Searches, and Reviews
7. Manage Human, Communication, and Compliance Risk
Operate Insider Risk and Communication Compliance Responsibly Use Information Barriers and Compliance Manager as Governed Controls
8. Protect Privacy, SharePoint, Microsoft 365, and AI
Secure SharePoint and Microsoft 365 Collaboration Paths Govern Microsoft 365 Copilot and Other Generative AI Protect Privacy and Support Data-Subject Workflows
9. Integrate, Report, and Operate Purview
Integrate Scanners, APIs, Reporting, and Multi-Cloud Sources Run Purview as a Production Security Service Turn DSPM Findings into Data Security Investigations
10. Design and Prove a Complete Purview Program
Build the Purview Target Architecture and Roadmap Capstone: Prove the Security Layer End to End
9. Integrate, Report, and Operate Purview

Turn DSPM Findings into Data Security Investigations

Connect posture discovery, risk context, investigations, remediation, and outcome measurement without treating a recommendation as a conclusion.

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In this lesson, you will learn to:

  • Triage a posture finding into a scoped investigation, proportionate remediation, and measurable improvement while preserving evidence and uncertainty.

Turn DSPM Findings into Data Security Investigations

This lesson explains how Data Security Posture Management and Data Security Investigations can connect visibility to an accountable, evidence-led remediation workflow.

Posture findings identify relationships that require judgment

Data Security Posture Management brings together information about sensitive data, exposure, users, applications, activities, and policies. A recommendation can reveal that important data is overshared, used through an AI application, or moving along a risky path. It is a starting point for analysis, not proof of breach or a completed control.

Validate the population, time window, data sources, licenses, freshness, classification quality, and denominator behind the finding. Identify the affected data, identities, applications, locations, permissions, and activities. Ask whether the risk comes from broad access, unsafe transfer, missing classification, weak policy, stale ownership, or incomplete telemetry.

Prioritize by impact, exposure, likelihood, exploitability, and business dependency. A small number of public links to regulated records may deserve faster action than thousands of low-sensitivity unlabeled files. Record alternative explanations and the evidence that would change priority.

An investigation must end in an owned and verified change

Open a data security investigation when the question, authority, and required evidence are clear. Define the suspected risk path, affected scope, decision deadline, collection sources, privacy constraints, and owner. Preserve relevant audit, DLP, access, label, endpoint, and AI activity evidence before remediation changes the environment.

Choose the smallest action that breaks the unsafe path: correct permissions, remove a sharing link, apply or repair a label, tune a detector, publish a policy, block a destination, onboard a device, replace an unmanaged workflow, or escalate a suspected incident. Record business impact, rollback, exceptions, and residual routes.

Close only after retesting the original path and monitoring recurrence. Measure time to owner, time to containment, affected population, evidence completeness, repeated exposure, exception age, and whether the risky action declined. Feed the result back into the posture objective, policy design, ownership, and training. This is how a dashboard observation becomes defensible risk reduction.

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