You’ll learn how to master DLP logic in Power Platform to prevent data leaks and safeguard your organization — directly inside the Microsoft cloud — in this episode.
Who this episode is for:
• You want practical strategies you can apply instantly
• You want real execution — not theory
• You want to unlock Microsoft 365, Power Platform, and Azure for real business outcomes
Scenario:
Sensitive data is slipping through unnoticed connectors, creating compliance risks across environments.
Step-by-step – what you’ll learn:
• What DLP logic in Power Platform truly protects against
• How to configure rules to catch hidden data flows
• Techniques to monitor and map data movement across environments
• Ways to combine DLP with other Microsoft tools for enhanced security and productivity
Tools + tech included:
• Microsoft 365 / Power Automate / Teams / SharePoint / Azure
• Data Loss Prevention (DLP) policies
• Advanced connector classification
• Real-time analytics and sandbox environments
Practical payoff:
• Reduce compliance risks
• Eliminate data leaks from shadow IT
• Gain clarity and visibility into data workflows
Open topical anchors:
productivity improvement • modern work enablement • digital operations • automation strategy • cloud-first transformation
Example business cases listeners can apply immediately:
• Catching invisible data flows between business and personal accounts
• Mapping high-risk connectors for payroll and customer data
• Testing DLP policies safely to avoid breaking critical workflows
Outcome statement:
By the end of this episode — you’ll have a clear strategy to spot blind spots, align your DLP policies with real-world workflows, and protect sensitive data across the Microsoft ecosystem.
Call-to-action:
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#riskassessment #hiddenrisks #dataprotection #dlplogic #dataleaks
CHAPTERS:
00:00 - Intro
00:30 - Why DLP Solutions Fail
04:49 - Getting Started with DLP
05:29 - If-Then Scenarios in DLP
10:42 - Connector Classifications in DLP
16:20 - Designing Adaptive DLP Policies
19:40 - Importance of a DLP Sandbox
20:15 - Iterating on DLP Policies
21:13 - Thinking in Systems for DLP
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