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
2. Discover, Map, and Curate the Data Estate

Design Data Map Scanning and Metadata Collection

Plan collections, source registration, credentials, scans, classification, and monitoring without confusing metadata discovery with data access.

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In this lesson, you will learn to:

  • Apply a repeatable method for design data map scanning and metadata collection in a licensed, governed, and testable Purview environment.

Design Data Map Scanning and Metadata Collection

This lesson develops a practical understanding of design data map scanning and metadata collection and connects design choices to supported capabilities, operational dependencies, user impact, and verifiable evidence.

A useful map begins with scope and ownership

Microsoft Purview Data Map captures metadata about assets across supported cloud, SaaS, database, storage, and on-premises sources. A scan can collect names, schemas, classifications, lineage, and relationships without turning the catalog into a copy of all underlying business data. This distinction is central: governance roles over metadata do not automatically provide access to source records.

Start with decisions the map must support. A financial-data program may need to find authoritative revenue datasets, show upstream sources, identify personal-data columns, and assign accountable owners. That purpose determines which sources, collections, scan rule sets, classifications, and refresh frequencies matter. Registering everything without stewardship creates an expensive inventory that users cannot trust.

Design collections around administrative boundaries, not merely the organization chart. Record scan identities, network paths, integration runtimes, secret rotation, source load windows, excluded schemas, sampling behavior, and ownership. The Data Map architecture and scanning guide provides the detailed deployment pattern.

Operate scans as a monitored ingestion service

A green scan status does not prove complete discovery. Compare expected and discovered assets, inspect classification coverage, investigate schema drift, and record sources that cannot be scanned. A credential can succeed while permissions expose only part of a database. A classifier can run while sampling misses rare sensitive values.

Use a scan runbook:

  1. Confirm the source owner, approved scope, and expected asset inventory.
  2. Test least-privilege connectivity and record the network path.
  3. Select or customize the scan rule set and excluded patterns.
  4. Run a bounded pilot; validate representative assets with the owner.
  5. Schedule refresh according to change rate and source capacity.
  6. Alert on failures, large count changes, stale scans, and classification drift.
  7. Reconcile decommissioned sources and rotate credentials.

When an API integration returns timeouts, reduce relationship expansion, paginate reads, and use small idempotent writes. The Data Map HTTP 408 guide explains how to recover without creating inconsistent metadata.

Resources