- Project Lead Chase Olson
- Client Celestica
- Date Aug 2024 - Oct 2024
- Coffee Consumed 160 Cups
Led the implementation of Microsoft Purview Data Loss Prevention (DLP) to enhance data security, prevent unauthorized sharing, and ensure regulatory compliance for a client.
- DLP Strategy Design: Developed a DLP strategy aligned with security goals to safeguard sensitive data such as PII, financial records, and intellectual property.
- Policy Creation: Designed and implemented DLP policies targeting critical data types like SSNs, bank details, credit card information, and proprietary data. Configured policies to prevent unauthorized sharing via email, cloud storage, and collaboration platforms.
- Role-Based Access Control (RBAC): Implemented RBAC to ensure only authorized personnel could access and share sensitive information, reducing risks from insider threats and unauthorized access.
- Email and File Scanning: Enabled DLP across Microsoft 365 services (Outlook, OneDrive), automatically scanning emails and files for sensitive data. Configured alerts and actions to block or restrict data sharing based on policies.
- Data Classification and Labeling: Used Purview’s classification and labeling to categorize data by sensitivity. Applied labels like “Confidential” to enforce DLP rules for specific data sets.
- Incident Response and Monitoring: Set up DLP reporting and alert mechanisms to detect and respond to potential data breaches. Provided IT teams with real-time insights into DLP incidents for timely responses to data sharing violations.
- User Education: Delivered training to educate employees on DLP policies, best practices for handling sensitive data, and the importance of data security.
- Compliance Alignment: Ensured DLP policies met regulatory requirements such as GDPR and HIPAA, reducing the risk of compliance violations.
- Improved Data Security: Strengthened security posture by preventing data leaks and improving the monitoring of sensitive information, reducing the likelihood of accidental or intentional data loss.