Complex Event Processing (CEP) is a technique for tracking, analyzing, and processing incoming streams of data in real time and generating a summarized report. Event processing-based platforms have built-in capabilities for filtering, storing, computing aggregates, and detecting patterns from incoming data. The underlying system will correlate the incoming streams of event data and trigger a process.
The main goal of CEP is to identify meaningful events and respond to them as quickly as possible. These events can be either opportunities or threats. It tracks and analyzes the stream of data about events and derives a conclusion from them.
Examples of Complex Event processing
- Regulatory Constraints
Report generation on daily transactions is needed for regulatory purposes.
- Fraud Detection
Credit card companies use CEP to detect fraud. Let’s say the same credit card is used to execute two different transactions within an hour time frame at a distance of greater than 200 Miles. We can CEP-based architecture to detect this in real-time.
- Aggregation
We can use CEP to generate aggregated reports at the end of the day at a certain fixed time.
- Weather Forecasting
CEP along with the Machine Learning algorithm is currently being used to do weather forecasting based on weather data.
- Internet of Things (IoT)
We can combine information coming from various IOT-based sensors and use CEP as an engine to predict the outcome. CEP can be used for real-time monitoring and analytics. An example would be identifying Guests/intruders in a smart home system.
- Retail based Application
E-commerce-based retailers can use the CEP engine to offer personalized recommendations based on shoppers’ shopping habits and GPS (Global Positioning) data.
Software Used for Processing Complex Events
There is a lot of software that can be used to build CEP-based applications. There are some tools that are vendor-based, whereas some are open sources. We need to choose the right software for the right use case. This choice depends upon the budget and skill set of the engineers that work in your company. Below is some common and popular software.
- Apache Spark Streaming
- Apache Samza
- Apache Flink
- Apache Twitter
- Microsoft Azure Stream Analytics/ Stream Insight
- Oracle Stream Analytics
- IBM Streams
- Amazon Kinesis
Conclusion
In this blog post, we learned about Complex Event Processing(CEP), its examples, and the software used for CEP.
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