Anomaly Detection for Global Scale at Netflix

The document discusses global scale anomaly detection in data engineering and analytics, highlighting challenges such as unrealistic expectations and limited analyst capacity. It emphasizes the need for smarter analytic products that can identify statistical anomalies and provide insights filtered by impact. A case study on payment processing illustrates the complexities involved, including high cardinality dimensions and numerous time series.