Speaker
Description
Event Pattern Matching (EPM) in real-time complex data processing refers to the technique of identifying and reacting to specific sequences of events within a continuous stream of data. It is commonly used in Complex Event Processing (CEP) systems to detect meaningful patterns or anomalies that occur across different data sources and over time.
This capability is essential in scenarios where large amounts of data are being generated continuously and require immediate or near-real-time analysis to extract actionable insights. Examples include financial markets, IoT sensors, network monitoring, and fraud detection.
In this lecture will provide an introduction to technologies behind Stream Processing (SP), Batch Processing (BP) and Complex Event Processing (CEP).
