Real-time event processing empowers enterprises to detect meaningful patterns in the real-time flow of events and to react to them in a timely manner. By detecting event patterns, it is possible to identify the most critical opportunities and risks.
Components of Pega 7 real-time event processing
Real-time event processing is implemented by using the following components:
- Stream Data Set – Processes a continuous data stream of events. It can take in high volumes of low-latency data. You can use this type of data set to save data to the stream and to browse data from the stream.
Event Strategy – A visual representation of processing logic that is applied to all incoming events. Event strategies can be used to specify patterns of events, query them across a data stream, and react to the emerging patterns.
Event Strategy canvas
Data Flow - Connects a data stream and static data sources to an event strategy. Data flows can be modified to support real-time runs, and can be used to manage data that is coming in at a high speed and to provide followup actions.
Data Flow canvas
In the primary Data set pattern, you must specify the data set from which you want to import data.
For real-time processing, you must select a Stream data set to provide a continuous data stream of events.
When the data enters a data flow, an event strategy that is referenced from the Event Strategy pattern queries for events patterns across the data stream and reacts to the emerging patterns.