Sensitive data now lives in terabytes and petabytes across cloud, SaaS, and on-prem systems that were never designed for full-content scanning. At that scale, traditional discovery patterns quietly break: brute-force classification becomes too expensive to run, regex-heavy rules miss real-world context, and "smart" sampling leaves most of your crown jewels uninspected. Meanwhile, regulators are increasingly explicit that probability is not a defense when something leaks.
In this session, Lightbeam Chief Architect Aditya Ramesh will break down what it actually takes to find and secure sensitive data at petabyte scale. He'll dissect the hidden failure modes of brute-force scanning and sampling, walk through the real compute and time costs of full discovery, and show where common DSPM approaches fall over in the terabyte-to-petabyte range.
From there, Aditya will share scalable patterns practitioners can steal: metadata-first inventories to map your data surface, semantic templates to avoid constant rescans, event-driven and incremental scanning to keep pace with change, and hybrid architectures that run close to where data lives. Attendees will leave with a practical mental model for building discovery pipelines that can keep up with growth instead of collapsing under it.
Receive 1 CPE credit and some great technical information!