Скачать или смотреть Product Demo: How Dynamic Data Masking Protects Sensitive Data from Analytics Users

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Overview
In this video, we explore Dynamic Data Masking (DDM) and how Mage Data helps organizations safeguard sensitive information while still allowing analytics users to access.

Key Topics Covered
✅ Business Driver: Analytics users need production data but shouldn't see sensitive information.
✅ Illustrative Example: Meet Paige, an analyst who needs data but must comply with privacy policies.

Mage Data’s 3-Step Solution
Step 1: Identify who the policy applies to (e.g., analytics users).
Step 2: Locate sensitive data within databases.
Step 3: Define protection mechanisms (e.g., redaction, encryption).

Benefits of DDM
✅ Dynamic & Transparent Masking: Ensures secure access without modifying underlying data.
✅ Realistic Anonymized Data: Keep data usability intact while protecting privacy.
✅ Flexible & Scalable: Supports context-preserving encryption, conditional masking, and applies rules across enterprise platforms.

Why It Matters
✔️ Helps businesses stay compliant with data privacy regulations.
✔️ Protects customer data without limiting analytics capabilities.
✔️ Seamless integration with existing data platforms.

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