A practical guide to real-time anomaly detection covering five SQL-based algorithms: out-of-range, timeout, rate-of-change, interquartile range (IQR), and Z-score. The post explains the challenges of applying traditional anomaly detection methods to streaming data, contrasts supervised vs. unsupervised approaches, and provides SQL code examples built on Tinybird (a ClickHouse-based platform). Use cases span flood warning systems, IoT monitoring, fraud detection, and more.
Table of contents
What is Anomaly Detection?Real-time Anomaly Detection: Challenges and Solutions5 Real-Time Anomaly Detection Algorithms with Example CodeClosing and Additional Resources740 Impressions