02 Microsoft Purview

Modern organizations generate and process enormous amounts of information across:

Email

Documents

Collaboration Platforms

Cloud Storage

Endpoints

Databases

SaaS Applications

Business Applications

Data Platforms

From a GRC perspective, the challenge is no longer simply:

Where Is
Our Data?

Organizations must understand:

What Data
Do We Have?

Where Is It?

Who Can
Access It?

Is It
Sensitive?

How Should
It Be Protected?

How Long
Should We
Keep It?

Can It
Leave the
Organization?

Are Users
Handling It
Appropriately?

Can We
Find It During
an Investigation?

Can We
Demonstrate
Compliance?

Microsoft Purview provides capabilities designed to help organizations discover, understand, classify, protect, govern, investigate, and manage information.

A simplified governance model looks like:

Enterprise Data
      ↓
Discover
      ↓
Classify
      ↓
Protect
      ↓
Control
      ↓
Retain
      ↓
Monitor
      ↓
Investigate
      ↓
Report

For a GRC professional, Microsoft Purview should be understood as part of the organization’s broader data governance, privacy, information protection, compliance, legal, and security operating model.

Learning Objectives

By the end of this lesson, you will be able to:

• Explain the role of Microsoft Purview.

• understand Purview from a GRC perspective.

• distinguish data governance from data protection.

• understand data discovery.

• understand data classification.

• understand sensitive information types.

• understand sensitivity labels.

• understand information protection.

• understand Data Loss Prevention.

• understand retention.

• understand records management.

• understand data lifecycle management.

• understand audit capabilities.

• understand eDiscovery.

• understand insider risk management.

• understand communication compliance concepts.

• understand compliance management.

• understand compliance assessments.

• understand compliance scoring concepts.

• understand data governance.

• understand data catalog concepts.

• understand data lineage.

• understand data ownership.

• understand privacy-related use cases.

• understand policy alerts and investigations.

• understand role-based access.

• design a practical Purview governance model.

• connect Purview capabilities with enterprise GRC processes.

1. What Is Microsoft Purview?

Microsoft Purview is a family of capabilities focused on areas such as:

Data Governance

Data Security

Information Protection

Data Loss Prevention

Data Lifecycle

Records Management

Audit

eDiscovery

Insider Risk

Compliance

The exact capabilities available to an organization depend on its Microsoft environment, licensing, configuration, and product evolution.

2. Purview from a GRC Perspective

A GRC professional should not think of Purview simply as:

Another
Microsoft Tool

Instead think:

Data
      ↓
Business Context
      ↓
Classification
      ↓
Policy
      ↓
Control
      ↓
Monitoring
      ↓
Evidence
      ↓
Compliance

3. The Data Governance Problem

Consider an organization with:

50,000 Employees

Millions of Documents

Thousands of Teams

Hundreds of Applications

Multiple Cloud Platforms

Multiple Countries

Sensitive information may exist across all of them.

Without governance, organizations may not know:

Where Sensitive
Data Exists

Who Owns It

Who Has Access

How It Moves

How Long It Exists

Whether It Is
Protected

4. Data Governance

Data governance establishes:

Ownership

Accountability

Classification

Quality

Protection

Retention

Usage

Lifecycle

for organizational data.

5. Data Governance Lifecycle

Data Created
      ↓
Discover
      ↓
Classify
      ↓
Assign Ownership
      ↓
Protect
      ↓
Use
      ↓
Share
      ↓
Retain
      ↓
Archive / Delete

6. Data Discovery

Before protecting sensitive information, organizations must identify:

Where It Exists

Discovery may involve:

Microsoft 365

Cloud Data

Databases

Data Lakes

Applications

Other Connected Sources

depending on the organization’s Purview implementation.

7. Data Inventory

A mature data governance program should understand:

Field	Example
Data Asset	Customer Database
Owner	Customer Operations
Classification	Confidential
Personal Data	Yes
Location	Cloud
Retention	7 Years
Access	Restricted
Regulatory Scope	Privacy / Contractual

8. Data Classification

Classification helps answer:

How sensitive or important is this information?

Example model:

Public

Internal

Confidential

Highly Confidential

9. Classification Example

Marketing Brochure
      ↓
Public

Internal Procedure
      ↓
Internal

Customer Information
      ↓
Confidential

Authentication Secrets
      ↓
Highly Confidential

10. Why Classification Matters

Classification can drive:

Access

Encryption

Sharing

DLP

Retention

Monitoring

Handling Requirements

11. Sensitive Information Types

Sensitive information types help identify particular patterns or categories of sensitive data.

Examples may include:

Financial Information

Government Identifiers

Payment Information

Health Information

Personal Information

depending on applicable definitions and configured detection mechanisms.

12. Sensitive Data Detection

Conceptually:

Document
      ↓
Content Inspection
      ↓
Sensitive Pattern
      ↓
Classification
      ↓
Policy

13. Example

Document contains:

Customer Name

Payment Information

Address

Contact Information

Detection may trigger:

Sensitive
Information
Policy

14. Sensitivity Labels

Sensitivity labels allow organizations to classify information and apply protection or handling expectations.

Example:

Public

General

Confidential

Highly Confidential

15. Label Architecture

Avoid creating:

50 Labels

that users cannot understand.

Prefer a manageable classification model.

Example:

Public

Internal

Confidential

Highly Confidential

with carefully designed subcategories only where necessary.

16. Label Example

Highly Confidential
      ↓
Restricted Sharing
      ↓
Encryption
      ↓
Access Restrictions

17. Manual Labeling

A user may classify a document:

Document
      ↓
Sensitivity Label
      ↓
Confidential

18. Automated Classification

Organizations may also configure mechanisms that detect sensitive information and apply or recommend classification.

Conceptually:

Content
      ↓
Detection
      ↓
Classification Rule
      ↓
Label

19. Information Protection

Information protection aims to ensure:

Sensitive Data

receives appropriate:

Classification

Access Controls

Encryption

Usage Restrictions

Monitoring

20. Protection Follows the Data

Traditional security often protects:

Network Boundary

Modern information protection increasingly focuses on:

The Data
Itself

21. Data Loss Prevention

Data Loss Prevention — DLP — helps organizations detect and control inappropriate movement or sharing of sensitive information.

A simplified workflow:

User Action
      ↓
Sensitive Data
Detected
      ↓
DLP Policy
      ↓
Evaluate
      ↓
Allow / Warn /
Block / Audit

22. DLP Example

Employee attempts to send:

Sensitive Customer Data

to:

External Recipient

Policy evaluates:

Data Type

Destination

User

Activity

Policy Conditions

23. Possible DLP Actions

Depending on policy design:

Allow

Audit

Warn

Require Justification

Restrict

Block

Alert

24. DLP Policy Design

A DLP policy should answer:

What Data?

Which Users?

Which Locations?

Which Activities?

Which Destinations?

What Action?

What Exception?

Who Is Alerted?

25. DLP Example Policy

IF

Payment Information
Is Detected

AND

Destination
Is External

THEN

Block Sharing

AND

Alert Security

26. DLP Locations

DLP policies may cover supported locations across the Microsoft information environment, depending on licensing and configuration.

Examples can include:

Email

Collaboration

Documents

Endpoints

27. Policy Tips

A policy may notify the user:

This document contains
sensitive information
and should not be shared
externally.

This provides:

Control
+
User Education

28. DLP False Positives

Poorly designed DLP can produce:

Too Many Alerts

User Frustration

Business Disruption

Alert Fatigue

29. DLP Tuning

A mature lifecycle:

Design
      ↓
Test
      ↓
Monitor
      ↓
Analyze
      ↓
Tune
      ↓
Enforce

30. Start in Monitoring Mode

For high-impact policies, organizations may first evaluate:

What Would
the Policy Do?

before broadly blocking business activities.

31. DLP Exception Management

Example:

Business Process
Requires External
Data Transfer

Instead of disabling DLP:

Documented Exception
      ↓
Risk Assessment
      ↓
Approval
      ↓
Compensating Controls
      ↓
Expiry

32. Data Lifecycle Management

Data should not exist forever simply because storage is inexpensive.

Organizations need:

Creation

Usage

Retention

Disposition

governance.

33. Retention

Retention determines:

How Long
Information
Must Be Kept

34. Retention Drivers

Retention requirements may originate from:

Law

Regulation

Contract

Business Need

Legal Hold

Internal Policy

35. Example Retention Schedule

Record Type	Retention
Security Logs	1 Year
Employee Records	Per HR/legal requirement
Financial Records	Per applicable requirement
Contracts	Contract + defined period
Investigation Records	Per policy

Actual periods must be determined by applicable organizational and legal requirements.

36. Retention Policy

Conceptually:

Information Type
      ↓
Retention Rule
      ↓
Keep
      ↓
Disposition

37. Over-Retention Risk

Keeping everything forever creates:

Privacy Risk

Legal Discovery Risk

Security Exposure

Storage Cost

Governance Complexity

38. Under-Retention Risk

Deleting too early may create:

Regulatory Violations

Legal Problems

Audit Gaps

Missing Evidence

39. Records Management

Some information becomes an official organizational record.

Examples:

Contracts

Financial Records

Regulatory Evidence

Corporate Decisions

Legal Records

40. Record Lifecycle

Created
      ↓
Declared Record
      ↓
Protected
      ↓
Retained
      ↓
Reviewed
      ↓
Disposed

41. Disposition Review

Before deleting certain records:

Retention Period
Ends
      ↓
Disposition Review
      ↓
Approve / Extend /
Investigate
      ↓
Disposition

42. Legal Hold

Normal retention may need to be overridden when information is subject to:

Litigation

Investigation

Regulatory Inquiry

43. eDiscovery

Electronic discovery helps authorized teams identify and manage information relevant to:

Legal Matters

Investigations

Regulatory Requests

44. Simplified eDiscovery Workflow

Case
      ↓
Custodians / Sources
      ↓
Preservation
      ↓
Search
      ↓
Collection
      ↓
Review
      ↓
Export / Production

Capabilities and workflows depend on the applicable Purview offering and organizational configuration.

45. eDiscovery Case

Example:

Case:
Contract Dispute

Potential information:

Email

Documents

Chats

Relevant User Data

46. Preservation

Relevant information may need to be preserved to prevent normal deletion processes from removing it.

Case
      ↓
Preservation
      ↓
Relevant Information
Retained

47. Search

Authorized investigators may define criteria such as:

Custodian

Date Range

Keywords

Data Sources

48. Investigation Governance

eDiscovery should use:

Authorization

Least Privilege

Case Management

Auditability

Legal Oversight

49. Audit

Audit capabilities can help authorized teams investigate activity across supported Microsoft services.

Examples of useful activities may include:

User Actions

Administrative Actions

File Activities

Sharing Activities

Security Events

Configuration Changes

50. Audit Use Case

Question:

Who Shared
This Sensitive
Document?

Audit investigation:

Document
      ↓
Activity
      ↓
User
      ↓
Time
      ↓
Action

51. Audit Evidence

Audit information can support:

Security Investigations

Compliance Assessments

Internal Audits

Legal Investigations

Incident Response

52. Audit Retention

Organizations should understand:

What Is Logged?

How Long?

Who Can Access It?

Can It Be Exported?

What Licensing Applies?

rather than assuming every activity remains available indefinitely.

53. Insider Risk

Not all data risks originate from external attackers.

Potential insider-related scenarios include:

Data Theft

Unauthorized Sharing

Sensitive Data Exfiltration

Policy Violations

Risky User Behavior

54. Insider Risk Model

Conceptually:

Signals
      ↓
Policy
      ↓
Potential Risk
      ↓
Alert
      ↓
Investigation
      ↓
Action

55. Insider Risk Requires Governance

These capabilities can involve highly sensitive employee information.

Therefore organizations should establish:

Privacy

Legal Oversight

HR Involvement

Authorization

Least Privilege

Investigation Procedures

56. Avoid Surveillance-First Thinking

The objective should be:

Manage Legitimate
Organizational Risk

within applicable:

Law

Policy

Privacy Requirements

Employment Requirements

57. Communication Compliance

Organizations may need to identify certain communication risks according to legitimate organizational and regulatory requirements.

Potential scenarios can include:

Regulated Communications

Policy Violations

Inappropriate Disclosure

Business Conduct Risk

58. Communication Compliance Workflow

Conceptually:

Communication
      ↓
Policy
      ↓
Potential Match
      ↓
Review
      ↓
Investigation
      ↓
Action

59. Privacy Controls

Purview capabilities can support parts of an organization’s privacy program through areas such as:

Data Discovery

Classification

Protection

Retention

Investigation

Governance

But technology does not replace:

Privacy Governance

Legal Interpretation

Data Processing Records

Risk Assessments

Organizational Accountability

60. Data Minimization

Privacy programs should ask:

Do We
Need This Data?

rather than:

Can We
Store It?

61. Data Subject Requests

Organizations handling privacy rights requests may need to locate relevant personal information across multiple systems.

A broader process might look like:

Request
      ↓
Identity Validation
      ↓
Data Discovery
      ↓
Review
      ↓
Legal Validation
      ↓
Response

62. Compliance Management

Purview’s compliance capabilities can help organizations organize compliance activities around:

Regulations

Assessments

Improvement Actions

Evidence

Responsibility

Progress

63. Compliance Assessment Model

Conceptually:

Regulation
      ↓
Assessment
      ↓
Requirements
      ↓
Improvement Actions
      ↓
Evidence
      ↓
Status

64. Improvement Action

An improvement action might represent:

Implement MFA

Configure DLP

Review Retention

Enable Logging

Document Procedure

65. Action Ownership

Every improvement action should have:

Owner

Status

Due Date

Evidence

Implementation Notes

66. Compliance Score

Compliance-management capabilities may provide scoring to help organizations understand progress against configured assessments and improvement actions.

Do not interpret:

High Score

as automatically meaning:

Fully Compliant

67. Why?

Compliance depends on:

Scope

Applicability

Evidence

Control Effectiveness

Legal Interpretation

External Assessment

A platform-generated score is a management indicator, not a universal certification.

68. Compliance Evidence

Evidence may include:

Configurations

Policies

Reports

Screenshots

Procedures

Assessment Results

69. Compliance Evidence Workflow

Improvement Action
      ↓
Implementation
      ↓
Evidence
      ↓
Review
      ↓
Assessment Status

70. Data Catalog

A data catalog helps organizations understand:

What Data
Assets Exist?

and their:

Meaning

Ownership

Classification

Relationships

Business Context

71. Data Asset

Examples:

Customer Database

HR Dataset

Payment Data Store

Sales Analytics Dataset

72. Data Asset Metadata

Useful metadata includes:

Name

Description

Owner

Source

Classification

Sensitivity

Business Domain

Relationships

73. Business Glossary

Different teams may use different terminology.

Example:

Customer

Client

Subscriber

Account Holder

A business glossary helps establish:

Common Meaning

74. Data Ownership

Every important data domain should have clear accountability.

Examples:

Customer Data
→ Customer Operations

Employee Data
→ Human Resources

Financial Data
→ Finance

75. Data Steward

A data steward may help maintain:

Data Definitions

Quality

Classification

Metadata

Governance

76. Data Lineage

Lineage helps answer:

Where did this data come from and where does it go?

77. Example Lineage

CRM
      ↓
Data Pipeline
      ↓
Data Lake
      ↓
Analytics Platform
      ↓
Executive Dashboard

78. Why Lineage Matters

If sensitive information originates in:

CRM

and moves into:

Data Lake

then into:

Analytics

protection requirements may need to follow that data across the lifecycle.

79. Data Mapping

For GRC and privacy teams:

System
      ↓
Data
      ↓
Owner
      ↓
Classification
      ↓
Processing
      ↓
Destination
      ↓
Retention

provides valuable governance context.

80. Data Domains

Large organizations can organize data into domains such as:

Customer

Finance

HR

Security

Operations

Product

81. Data Product Concept

Modern data governance may organize reusable data around business-oriented data products.

A GRC professional should ask:

Who Owns It?

What Data
Does It Contain?

Is It Sensitive?

Who Can
Use It?

Where Does
It Come From?

What Controls
Apply?

82. Access Governance

Sensitive data governance requires:

Right User

Right Data

Right Purpose

Right Time

83. Excessive Access

Example:

5,000 Employees

can access:

Customer Financial
Dataset

but only:

150

need it.

This creates:

Excessive
Data Exposure

84. Classification + Access

Highly Confidential
      ↓
Restricted Group
      ↓
Strong Authentication
      ↓
Monitoring

85. Classification + DLP

Confidential
      ↓
External Sharing
      ↓
DLP Policy
      ↓
Warning / Block

86. Classification + Retention

Record Type
      ↓
Classification
      ↓
Retention Rule
      ↓
Disposition

87. Integrated Data Governance

A mature model connects:

Discover
      ↓
Classify
      ↓
Protect
      ↓
Monitor
      ↓
Retain
      ↓
Investigate

rather than operating each capability independently.

88. GRC Integration

Purview does not have to operate separately from the organization’s GRC program.

Example:

GRC Requirement
      ↓
Data Protection
Control
      ↓
Purview Policy
      ↓
Monitoring
      ↓
Evidence
      ↓
Control Assessment

89. Example — DLP Control

Control:

DLP-001

Sensitive payment data
must not be transmitted
to unauthorized external
destinations.

Implementation:

Purview DLP
Policy

90. Evidence

Potential evidence:

DLP Configuration

Policy Scope

Policy Status

Alerts

Exceptions

Testing Results

91. Control Assessment

Control
      ↓
Purview Configuration
      ↓
Evidence
      ↓
Testing
      ↓
Conclusion

92. Example — Retention Control

Control:

RET-001

Regulated records
must be retained
according to the
approved retention
schedule.

Implementation:

Retention
Configuration

93. Example — Classification Control

Control:

DAT-001

Sensitive information
must be classified
according to the
enterprise classification
standard.

Implementation:

Sensitivity Labels
+
Classification Policies

94. Example — Audit Control

Control:

LOG-001

Relevant user and
administrative activities
must be logged and
available for investigation.

Implementation may include:

Audit Capabilities
+
Retention
+
Access Governance

95. Evidence Automation

Instead of asking every quarter:

Send Screenshot
of DLP Policy

organizations may design automated evidence collection where technically and operationally appropriate.

Purview
      ↓
Configuration Data
      ↓
Evidence Repository
      ↓
Control Assessment

96. Continuous Compliance

Example:

Sensitive Data
      ↓
DLP
      ↓
Policy Events
      ↓
Monitoring
      ↓
Exceptions
      ↓
GRC Issue

97. Alert Management

A policy may produce:

Thousands
of Events

Not every event should automatically become:

GRC Finding

98. Event Triage

Event
      ↓
Alert
      ↓
Triage
      ↓
Investigation
      ↓
Confirmed Issue
      ↓
GRC Finding

99. Severity

Define criteria based on factors such as:

Data Sensitivity

Volume

Destination

User

Business Context

Regulatory Impact

100. Example

1 Internal Document
Sent to Approved Partner

may differ greatly from:

50,000 Customer Records
Uploaded to Personal
Cloud Storage

101. Exception Governance

A business may need legitimate exceptions.

Create:

Exception Request
      ↓
Risk Assessment
      ↓
Data Owner
      ↓
Security / Privacy
      ↓
Approval
      ↓
Expiry

102. Policy Ownership

Every important policy should have:

Business Owner

Technical Owner

Review Frequency

Scope

Exception Process

103. Purview Roles

Organizations may have roles such as:

Compliance Administrator

Data Governance Team

Privacy Team

Security Team

Legal Team

Data Owner

Records Manager

Investigator

Auditor

104. Least Privilege

Some Purview capabilities provide access to highly sensitive information.

Examples:

Employee Communications

Investigation Data

Legal Cases

Audit Activity

Sensitive Documents

Access should therefore be tightly controlled.

105. Separation of Duties

Avoid one individual having unnecessary ability to:

Create Policy

Approve Exception

Investigate Alert

Delete Evidence

Close Finding

106. Privacy by Design

Before enabling monitoring capabilities ask:

What Is
the Purpose?

Is It
Necessary?

Is It
Proportionate?

Who Can
See Results?

How Long
Is Data Kept?

What Legal
Requirements Apply?

107. Purview Governance Model

A practical operating model:

GRC
      ↓
Requirements

Privacy
      ↓
Data Protection

Legal
      ↓
Retention / eDiscovery

Security
      ↓
Monitoring / DLP

Data Office
      ↓
Data Governance

Business
      ↓
Ownership

108. Implementation Sequence

A practical implementation may follow:

Phase 1
Governance

Phase 2
Data Discovery

Phase 3
Classification

Phase 4
Protection

Phase 5
DLP

Phase 6
Retention

Phase 7
Audit

Phase 8
Investigation

Phase 9
Compliance

Phase 10
Automation

109. Phase 1 — Governance

Define:

Stakeholders

Data Owners

Policy Owners

Classification Standard

Retention Standard

Exception Governance

110. Phase 2 — Discovery

Understand:

Data Sources

Data Assets

Sensitive Data

Owners

Locations

111. Phase 3 — Classification

Establish:

Classification Levels

Sensitive Information Types

Label Taxonomy

Handling Requirements

112. Phase 4 — Protection

Define:

Encryption

Access

Sharing

Usage Restrictions

based on classification.

113. Phase 5 — DLP

Start with:

Priority Data

High-Risk Activities

Monitoring

Testing

Tuning

before broad enforcement.

114. Phase 6 — Retention

Define:

Record Categories

Retention Periods

Disposition

Legal Hold

Ownership

115. Phase 7 — Audit

Determine:

Required Activities

Retention

Investigation Access

Export Requirements

116. Phase 8 — Investigation

Establish:

Case Governance

Authorization

Evidence Handling

Escalation

117. Phase 9 — Compliance

Map:

Requirements

Controls

Improvement Actions

Evidence

Assessment Status

118. Phase 10 — Automation

Automate appropriate:

Classification

Evidence

Alerts

Reporting

Compliance Monitoring

119. Common Mistake — Deploying Labels First

Weak approach:

Create 30 Labels
      ↓
Publish to Everyone

Better:

Understand Data
      ↓
Classification Standard
      ↓
Business Requirements
      ↓
Simple Labels
      ↓
Pilot
      ↓
Deploy

120. Common Mistake — Too Many Labels

Users confronted with:

Public

Internal

Internal Restricted

Confidential

Confidential Finance

Confidential HR

Confidential Legal

Restricted

Restricted Critical

...

may simply select labels incorrectly.

121. Common Mistake — Blocking Too Early

Aggressive DLP deployment may:

Break Business
Processes

Start with:

Understand
      ↓
Monitor
      ↓
Tune
      ↓
Enforce

where appropriate.

122. Common Mistake — No Data Owners

Technology cannot determine every business decision.

Someone must decide:

Is This Data
Sensitive?

Who Should
Access It?

How Long
Should It Exist?

123. Common Mistake — Keep Everything Forever

This increases:

Privacy Risk

Security Risk

Legal Risk

Cost

124. Common Mistake — Delete Everything Quickly

This creates:

Legal Risk

Compliance Risk

Evidence Gaps

125. Common Mistake — Compliance Score = Compliance

Avoid:

Compliance Score:
95%

Therefore:
Compliant

Instead:

Score
+
Evidence
+
Control Effectiveness
+
Scope
+
Professional Assessment

126. Common Mistake — Alert = Incident

Purview alert:

Potential
Policy Violation

does not automatically equal:

Confirmed
Security Incident

Triage is required.

127. Common Mistake — Technology-Only Privacy

Privacy is not simply:

Deploy Purview

Privacy requires:

Governance

Law

Process

Transparency

Accountability

Data Management

Technology

128. Example End-to-End Scenario

Organization handles:

Customer Payment
Information

First:

Discover Data

Then:

Classify
      ↓
Confidential

Then:

Sensitivity Label

Then:

DLP Policy

Then:

Retention Policy

Then:

Monitoring

Then:

Evidence

Then:

GRC Assessment

129. DLP Event Scenario

Employee attempts:

Upload Customer
Payment Dataset

to:

Personal
Cloud Storage

Workflow:

Sensitive Data
Detected
      ↓
DLP Policy
      ↓
Block
      ↓
Alert
      ↓
Triage
      ↓
Investigation
      ↓
Confirmed Issue
      ↓
GRC / Security Action

130. Retention Scenario

Contract:

Created
      ↓
Classified
      ↓
Retention Applied
      ↓
Business Lifecycle
      ↓
Retention Ends
      ↓
Disposition Review
      ↓
Delete / Extend

131. Investigation Scenario

Security asks:

Who Downloaded
the Sensitive
Dataset?

Investigator uses authorized audit capabilities to determine:

User

Action

Timestamp

Object

Activity

and correlates this with other investigation evidence.

132. GRC Scenario

Requirement:

Sensitive Customer
Data Must Be
Protected From
Unauthorized Disclosure

Control:

DLP-001

Technology:

Microsoft Purview
DLP

Evidence:

Policy Configuration

Policy Scope

Testing

Alert History

Exceptions

Assessment:

Effective /
Ineffective

Microsoft Purview Operational Checklist

Governance

• data governance model established.

• data owners identified.

• classification standard approved.

• policy owners assigned.

• legal requirements identified.

• privacy requirements identified.

• exception process established.

Data Discovery

• important data sources identified.

• sensitive data locations understood.

• data assets cataloged where appropriate.

• data owners mapped.

• business context documented.

Classification

• classification levels defined.

• sensitive information categories identified.

• label taxonomy designed.

• handling requirements defined.

• user guidance created.

Information Protection

• sensitive information protected.

• access requirements defined.

• sharing requirements defined.

• encryption requirements evaluated.

• protection aligned with classification.

DLP

• high-risk data identified.

• DLP use cases documented.

• locations identified.

• policy conditions defined.

• policy actions defined.

• pilot completed.

• false positives evaluated.

• policies tuned.

• exceptions governed.

• alerts monitored.

Retention

• retention schedule established.

• legal requirements validated.

• record categories defined.

• retention policies configured.

• disposition process established.

• legal hold requirements addressed.

Audit

• required audit activities identified.

• retention understood.

• investigation roles defined.

• access restricted.

• evidence-handling process established.

eDiscovery

• legal governance established.

• authorized users identified.

• case procedures documented.

• preservation procedures established.

• evidence access controlled.

Insider Risk

• legitimate risk scenarios defined.

• privacy review completed.

• legal review completed.

• investigation roles restricted.

• escalation procedures documented.

Compliance

• applicable assessments identified.

• improvement actions assigned.

• evidence maintained.

• action owners assigned.

• compliance indicators reviewed appropriately.

GRC Integration

• Purview controls mapped to GRC controls.

• evidence requirements defined.

• policy ownership aligned.

• exceptions connected to GRC.

• confirmed issues routed appropriately.

• continuous monitoring opportunities identified.

Microsoft Purview Deliverables

After completing this lesson, you should be able to design:

01 Data Governance Model

02 Data Classification Standard

03 Sensitivity Label Architecture

04 Sensitive Data Inventory

05 DLP Policy Matrix

06 Retention Schedule

07 Records Management Model

08 Audit Governance Model

09 eDiscovery Governance Workflow

10 Insider Risk Governance Model

11 Compliance Assessment Model

12 Purview-to-GRC Control Mapping

13 Purview Evidence Matrix

14 Purview Governance Dashboard

Practical Activity — Data Classification

Classify:

Marketing Brochure

Employee Directory

Customer Database

Payment Information

Security Credentials

Determine:

Classification

Owner

Access

Sharing

Protection

Retention

Practical Activity — Build a DLP Policy

Scenario:

The organization processes:

Payment Information

Create a policy covering:

Data Type

Users

Locations

External Sharing

Policy Action

User Notification

Alert

Exception

Escalation

Practical Activity — Retention

Create a retention matrix for:

Contracts

Employee Records

Security Logs

Customer Records

Financial Records

Investigation Evidence

Document:

Owner

Retention Trigger

Retention Period

Legal Basis

Disposition

Practical Activity — Purview GRC Mapping

Requirement:

Sensitive customer
information must be
protected against
unauthorized disclosure.

Create:

Requirement
      ↓
Control Objective
      ↓
DLP Control
      ↓
Purview Configuration
      ↓
Evidence
      ↓
Assessment

Practical Activity — DLP Investigation

Scenario:

Employee Attempts
to Transfer

10,000 Customer Records

to an External
Personal Destination

Determine:

DLP Detection

Policy Action

Alert Severity

Triage

Investigation

Evidence

Escalation

GRC Impact

Practical Activity — Design Purview Governance

Define responsibilities for:

GRC

Security

Privacy

Legal

HR

Data Governance

Records Management

Business Owners

IT

Then determine who:

Defines Classification

Owns Data

Configures DLP

Approves Exceptions

Reviews Alerts

Runs Investigations

Defines Retention

Approves Disposition

Provides Audit Evidence

Microsoft Purview GRC Mindset

When working with Purview, ask:

What Data
Do We Have?

Where Is It?

Who Owns It?

Why Do
We Need It?

Is It
Sensitive?

What Classification
Applies?

Who Should
Access It?

Can It Be
Shared Externally?

Should It
Be Encrypted?

What DLP
Controls Apply?

How Long
Must We
Keep It?

When Should
It Be Deleted?

Could It Be
Under Legal Hold?

What Activity
Must Be Logged?

Who Can
Investigate?

What Privacy
Constraints Apply?

What Happens
When a Policy
Triggers?

Is It an
Alert or a
Confirmed Issue?

What Exceptions
Are Allowed?

Who Approves
Exceptions?

What Evidence
Demonstrates
the Control?

Can Evidence
Be Automated?

Which GRC
Requirement Does
This Support?

Can We Demonstrate
That the Control
Actually Works?

That is the mindset of a GRC professional using Microsoft Purview.

Key Takeaways

• Microsoft Purview supports multiple capabilities related to data governance, information protection, compliance, investigation, and data lifecycle management.

• Data should first be understood before organizations attempt to protect it.

• Classification provides the foundation for many information-protection decisions.

• Sensitivity labels can communicate classification and support protection requirements.

• DLP helps detect and control inappropriate movement of sensitive information.

• DLP policies should be tested and tuned before aggressive enforcement where appropriate.

• DLP alerts require triage and do not automatically represent confirmed incidents.

• Retention should balance legal, regulatory, business, privacy, and security requirements.

• Keeping information forever can create significant organizational risk.

• Records management provides additional governance for official records.

• eDiscovery supports authorized legal and investigative workflows.

• Audit information can provide important evidence for investigations and compliance assessments.

• Insider-risk capabilities require strong privacy, legal, HR, and access governance.

• Compliance scores should be treated as management indicators rather than automatic proof of regulatory compliance.

• Data catalogs and metadata help organizations understand their information assets.

• Data lineage helps organizations understand how information moves between systems.

• Data owners provide business accountability for important information.

• Purview controls can be mapped into an enterprise GRC control framework.

• Purview configuration and monitoring information can become evidence for control assessments.

• Continuous monitoring can help organizations move beyond point-in-time compliance.

• Technology should support privacy and GRC governance rather than replace them.

• A strong Purview implementation starts with governance, data ownership, classification, and policy design before large-scale automation.

Knowledge Check

Before continuing, make sure you can answer:

1. What is Microsoft Purview?

2. What is data governance?

3. Why is data discovery important?

4. What is data classification?

5. What is a sensitive information type?

6. What is a sensitivity label?

7. How can classification influence protection?

8. What is Data Loss Prevention?

9. What conditions should a DLP policy consider?

10. Why should DLP policies be tuned?

11. What is a DLP false positive?

12. Why can monitoring before enforcement be useful?

13. What is data lifecycle management?

14. What determines retention requirements?

15. What risks are created by over-retention?

16. What risks are created by under-retention?

17. What is records management?

18. What is a legal hold?

19. What is eDiscovery?

20. Why should eDiscovery access be restricted?

21. How can audit data support GRC?

22. What is insider risk management?

23. Why does insider-risk monitoring require privacy governance?

24. What is compliance management?

25. Why does a high compliance score not automatically prove compliance?

26. What is a data catalog?

27. What is data lineage?

28. What is the role of a data owner?

29. How can Purview support enterprise GRC controls?

30. What evidence could demonstrate that a DLP control operates effectively?

31. What is the difference between a DLP alert and a confirmed GRC issue?

32. How should policy exceptions be governed?

33. Why is least privilege particularly important for investigation capabilities?

34. How can Purview support continuous compliance?

35. Why should governance come before automation?

What’s Next?

➡️ Next: 03 — Microsoft Defender Compliance

In the next lesson, you will examine how security posture, threat protection, vulnerability information, cloud security findings, identity signals, endpoint security, and security monitoring can contribute to enterprise GRC and continuous compliance.

You will explore the relationship:

Security Controls
      ↓
Security Telemetry
      ↓
Configuration
      ↓
Control Monitoring
      ↓
Evidence
      ↓
Compliance Assessment
      ↓
Risk
      ↓
Remediation

The focus will be on how GRC professionals can translate technical security evidence into control assurance, compliance reporting, risk decisions, remediation tracking, and continuous monitoring.