Scalable data classification for security and privacy

What this post added

Introduced a scalable data classification system that uses multiple data signals, a scalable system architecture, and machine learning to detect semantic types within Facebook at scale. The system handles both persistent data (via Bernoulli sampling, feature extraction, and ML classification) and online data (via a real-time prediction API). It incorporates a modular PyTorch-based ML model for unstructured data classification and aims to provide flexibility for adding new data type detections with low latency and tight memory constraints.