Merge pull request #53264 from riswinto/main

change wording for unit handoffs

Author: prmerger-automator[bot]

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/adaptive-protection-data-loss-prevention.md

@@ -59,3 +59,4 @@ Extending DLP with adaptive behavior makes sense when:
 - Static policies no longer scale with real usage patterns
 
 When applied intentionally, risk-based behavior extends DLP capabilities without sacrificing clarity or control.
+

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/define-policy-detection.md

@@ -74,4 +74,4 @@ This includes workflows where:
 
 In these cases, detection quality matters more than aggressive enforcement. Clear, accurate detection helps ensure policies respond to real risk instead of incidental use.
 
-With detection defined, the next step is deciding where the policy should apply and who it should affect.
+With detection defined, scope becomes the deciding factor for whether those signals create insight or noise.

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/guided-walkthrough-create-policy.md

@@ -211,9 +211,11 @@ Understanding how policy type, location, detection, actions, and simulation mode
 
 ## Additional scenarios
 
-This walkthrough focuses on a file-based sharing scenario to show how DLP policy decisions appear during creation.
+This walkthrough uses a file-sharing scenario to illustrate how DLP policy decisions come together during creation.
 
-The Microsoft documentation includes additional guided scenarios that apply the same concepts to other locations and data types. These scenarios are most closely aligned with the topics covered here:
+The same decision process applies to other locations and data types. Microsoft documentation includes guided scenarios that show how these concepts translate to email, SharePoint, OneDrive, and other common risk patterns.
+
+These scenarios apply the same policy decision patterns in different contexts:
 
 - [Create and deploy data loss prevention policies](/purview/dlp-create-deploy-policy?azure-portal=true)
 - [Help prevent sharing sensitive items via SharePoint and OneDrive with external users](/purview/dlp-create-policy-spo-odb-external?azure-portal=true)

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/manage-policies.md

@@ -93,4 +93,4 @@ Frequent alerts don't automatically indicate failure. In many cases, they highli
 
 Viewed this way, alerts act as feedback rather than punishment. They help guide thoughtful updates that improve protection while minimizing disruption.
 
-Understanding how to interpret and respond to alerts is the next step in managing DLP effectively.
+When static rules no longer scale with behavior, enforcement needs additional context.

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/policy-actions.md

@@ -71,4 +71,4 @@ Patterns in justifications can help answer questions like:
 
 Using this feedback helps improve policy quality over time.
 
-With actions defined, the policy is ready to be validated and refined before enforcement.
+Any action choice carries assumptions, and those assumptions need to be tested before enforcement.

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/policy-intent.md

@@ -44,4 +44,4 @@ When policy behavior aligns with real workflows:
 - Users are more likely to understand enforcement decisions
 - Policies act as guardrails instead of obstacles
 
-With clear intent and well-defined boundaries, policy creation becomes a deliberate design exercise rather than a trial-and-error configuration task.
+Once intent is clear, the next constraint becomes how much control the policy needs from the start.

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/policy-scope.md

@@ -82,4 +82,4 @@ For example, a policy might apply to browser-based AI tools while allowing appro
 
 Rather than blocking entire categories of activity, deliberate scoping helps ensure policies address risky behavior without preventing acceptable use.
 
-With scope defined, the next step is deciding how the policy should respond when risky activity occurs.
+Once scope is set, enforcement choices determine whether protection guides behavior or disrupts it.

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/policy-validation.md

@@ -79,4 +79,4 @@ Once enforced, policies should continue to be reviewed and refined as:
 
 Viewing validation as the beginning of a lifecycle helps keep policies relevant and effective over time.
 
-With validation complete, you can move the policy into enforcement with confidence in how it behaves.
+Validation confirms readiness, but real environments continue to change once enforcement begins.

learn-pr/wwl-sci/purview-data-loss-prevention-create-manage-policies/includes/template-custom-policy.md

@@ -58,4 +58,4 @@ Clear naming helps:
 
 This matters even more as policies grow in number and complexity.
 
-With a clear starting point and well-defined intent, you're ready to move from planning into defining what the policy actually detects.
+The starting point defines how much freedom you have, but detection determines whether the policy actually reflects risk.