Discovery And Protection of Your Data

In this video, Dan Johnson walks through the core data protection capabilities of the Protegrity AI Developer Edition. We transition from simple data discovery and redaction to more advanced workflows: protecting, unprotecting, encrypting, and decrypting sensitive PII (Personally Identifiable Information).

What You’ll Learn:

• API Registration: A quick walkthrough of registering for your API keys and setting up your environment variables (Email, Password, and API Key) in your terminal.
• Tokenization vs. Redaction: See how the "Find and Protect" command goes beyond simple redaction by tokenizing data, allowing for more flexibility in how data is handled across workflows.
• Role-Based Access Control (RBAC): We demonstrate how to apply permission schemas. See the difference in results when a Super User unprotects data to see the raw value versus a standard user who remains restricted to the protected or encrypted format.
• Encryption & Decryption: A look at the encryption flags and how to securely manage data that requires high-level cryptographic protection.
• Command Line Help: How to navigate the built-in help commands to understand various flags and sample application parameters.

Timestamps:

[00:00:49] - Navigating the GitHub repository and samples
[00:01:31] - Registering for API keys and environment setup
[00:03:52] - Running the "Find and Protect" sample on PII data
[00:04:19] - Demonstrating the unprotect workflow (Tokenized to Original)
[00:05:02] - Applying permissions (Super User vs. Standard User)
[00:06:36] - Implementing Encryption and Decryption flags
[00:08:09] - Exploring the Help command and parameter options

Resources:

GitHub Repository: Follow along with the Python SDK and sample applications featured in this video.
Next Video: Stay tuned for our next installment, where we’ll dive into semantic guardrails to add an additional layer of protection to your AI and ML workflows.

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