Episode 101 — Use analytics to detect drift, anomalies, and control breakdown trends (Domain 3D)
This episode focuses on using analytics as an audit technique to detect drift, anomalies, and control breakdown trends, because Domain 3D expects you to go beyond spot checks and prove what is happening over time. You’ll learn how to use trend analysis across model performance, outcome distributions, exception rates, manual overrides, and complaint signals to identify early warnings that controls are weakening or that the operating environment has changed. We’ll cover how analytics supports audit conclusions by helping you select higher-risk samples, validate whether monitoring thresholds are meaningful, and detect “silent failures” where metrics look fine in aggregate but break down across segments or specific decision types. You’ll also learn how to tie analytic results back to evidence sources like version histories, change tickets, lineage artifacts, and monitoring configurations so findings are defensible and reproducible. By the end, you should be able to answer AAIA scenarios by choosing analytic approaches that reveal control effectiveness and emerging risk, not just produce charts that no one can act on. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
