Microsoft Purview: Sensitive Info Types

Key insights

• Custom sensitive info types in Microsoft Purview: This video explains how to define patterns and rules that identify data not covered by built-in templates.
  It shows why these custom types matter for classification and protection across Microsoft 365.
• Why use them: Custom types deliver tailored detection that fits your organization's formats, improve compliance accuracy, and enable automated actions.
  They help avoid false positives and capture business-specific data patterns.
• Core creation steps: Identify sensitive data needs, translate them into patterns (keywords, regex, keyword proximity), then create and publish types in the Purview portal or via PowerShell.
  Validate definitions in test mode before full deployment.
• Advanced detection: Use document fingerprinting, exact data match, and trainable classifiers to detect complex or duplicated content.
  Enable OCR to find sensitive text inside images and scanned documents.
• Integration and automation: Associate custom types with sensitivity labels and auto-labeling policies to apply protection automatically.
  Combine with data scanning tools and cloud app controls for broader enforcement.
• Best practices and exam tips: Start in report-only mode, use representative sample data to test and refine rules, monitor results with Data Explorer, and map rules to compliance requirements.
  These steps align with SC-401 objectives for practical exam scenarios.

Overview of the Video

In a recent YouTube video, Peter Rising [MVP] explains how to create and manage custom sensitive info types within Microsoft Purview as part of SC-401 exam preparation. The video frames this work as essential for administrators who need to map organizational data protection requirements into practical detection rules. Consequently, viewers receive both conceptual context and hands-on guidance aimed at real-world scenarios.

Rising emphasizes that custom detection extends built-in templates and supports compliance goals in diverse environments. He outlines key steps such as defining patterns, testing in report mode, and integrating classifications with labels and policies. As a result, the segment offers a focused walkthrough that balances theory with operational detail.

Core Concepts Covered

The video starts by defining what custom sensitive info types are and why they matter for Microsoft 365 data governance. Rising explains that these types combine patterns, keyword lists, and advanced classifiers to detect sensitive content not covered by default rules, which helps organizations tailor protection to their needs. Thus, the approach supports both compliance and automated data handling across cloud services.

He also highlights complementary detection methods such as document fingerprinting and exact data match, which together increase accuracy beyond simple regular expressions. Moreover, the tutorial covers using optical character recognition (OCR) to detect sensitive text in images or scanned files. Therefore, the video positions multiple signals as part of a layered detection strategy.

How to Create and Manage Custom Sensitive Info Types

Rising walks through the practical steps of building a custom info type in Purview’s compliance portal and via PowerShell, demonstrating how to convert organizational requirements into rule definitions. He shows how to combine regex patterns, anchor keywords, and confidence thresholds so that rules match real data without generating excessive false positives. After creation, he stresses testing in report only mode to validate behavior before enforcement, which reduces operational risk.

Additionally, the video explains integration paths with sensitivity labels and auto-labeling policies to enable automated protection and lifecycle controls. Rising also points out monitoring options, recommending regular review of classification results using Purview’s explorer tools to refine rules over time. This continuous improvement loop helps maintain detection accuracy as business data and formats evolve.

Tradeoffs and Challenges

Rising acknowledges important tradeoffs when designing custom info types, primarily between detection sensitivity and false positives. Tightening rules can catch more targeted items but may mislabel benign content, which disrupts workflows and burdens administrators with remediation. Conversely, loose rules reduce false alarms but risk missing critical exposures, so teams must balance strictness and usability carefully.

He further discusses practical challenges such as managing performance and scale, handling diverse file formats, and accommodating multilingual data. Training or tuning advanced classifiers requires representative sample data, which can be hard to collect while respecting privacy. Therefore, the video recommends staged rollouts, stakeholder testing, and governance oversight to mitigate these risks effectively.

Practical Recommendations and Next Steps

To conclude, Rising recommends a phased approach: identify sensitive data patterns, create prototypes, test in report mode, and then apply policies gradually while monitoring results. He advises teams to use a combination of pattern matching, document fingerprinting, and trainable classifiers to improve coverage, and to enable OCR where images are common. By following this sequence, organizations can minimize disruption while increasing protection.

Finally, Rising suggests documenting definitions and audit trails to support compliance reporting and future tuning. He encourages administrators to leverage Purview’s monitoring tools and to align classification work with broader security and data governance programs. Consequently, the video serves as a practical guide for SC-401 candidates and practitioners aiming to strengthen Microsoft 365 data protection in production environments.

Keywords

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