Offering for Data Protection with Microsoft Purview

Harman data governance and data protection offering using Purview within the Azure ecosystem. Deploy Microsoft Purview solutions tailored to the specific needs of the organization. Configure Purview for data cataloging, lineage, and classification. Integrate with enterprise systems (e.g., Azure, Power BI, SAP). Provide comprehensive training and ongoing support to ensure effective use of Purview. Operationalize governance with automated workflows. Ensure enterprise-wide adoption and compliance.

1. HOW PURVIEW HELPS IN SECURING THE DATA

1. SENSITIVE DATA PROTECTION: Microsoft Purview protects sensitive data across clouds, apps, and devices using discovery, classification, and encryption tools.
2. DATA CLASSIFICATION: Tools like sensitive info types and classifiers help identify and monitor sensitive data and user actions.
3. ENCRYPTION: Double Key and Customer Key encryption secure data, ensuring only authorized users can decrypt it.
4. DATA LOSS PREVENTION: Prevents accidental sharing of sensitive data with policies that monitor, and block based on conditions.
5. INSIDER RISK MANAGEMENT: Identifies and mitigates risky user activities through Microsoft 365 and Graph logs.
6. INFORMATION BARRIERS: Restricts communication between groups to prevent conflicts of interest in regulated sectors.
7. PRIVILEGED ACCESS: Limits ongoing access to sensitive data with just-in-time permissions, reducing breach risks.

1. STRATEGY FOR IMPLEMENTING MICROSOFT PURVIEW DEFINE STRATEGY

• Set Goals: Improve data quality, ensure compliance, enhance security.
• Align with Business: Support overall business goals.

1. KEY FEATURES

• Data Map & Catalog: Visualize data landscape.
• Automated Discovery: Discover and catalog data across environments.
• Classification & Labels: Identify and protect sensitive data.

1. KEY SOLUTIONS INCLUDE:

• Data Classification and Protection: Automatically classify and protect sensitive data, like credit card numbers, ensuring only authorized access.
• Data Loss Prevention (DLP): Monitor and block unauthorized sharing of sensitive data through email, Teams, etc.
• Insider Risk Management: Detect and mitigate insider threats by identifying risky behavior patterns.
• Data Lifecycle Management: Implement retention policies to manage data from creation to deletion, such as deleting emails older than seven years.

1. BEST PRACTICES

• Domains & Collections: Organize data governance structure.
• Automation: Reduce manual effort, keep catalog updated.
• Security: Implement network security measures.