Description
Anomaly Detection in Data Streams uses machine learning algorithms to monitor and analyze real-time data flows to spot unexpected deviations or outliers that could indicate issues such as fraud, system failures, or data quality concerns. AI models can be trained to recognize normal data behavior and alert stakeholders when anomalies occur, enabling rapid intervention and minimizing potential damage or disruptions.
