원문정보
초록
영어
Individual data might not be thought of as that important for business purposes. However, Big Data analytics use cases are increasing, because individual data can become a valuable data aggregate from which any hidden information can be found, once it’s collected into large volumes. Big Data. Known as one of conventional Big Data analytics technologies, Hadoop is a widely accepted technology to analyze structured/ unstructured Big Data to date. However, Hadoop has a high possibility for response time latency with larger data because of batch processing systems, which makes it difficult to do real time analysis for massive amounts of high speed event data under the current business environment and market conditions.
In this paper, open source CEP (Complex Event Processing)-based technologies are used as an alternative for rapidly changing business, thereby developing the real time analytics system that enables us to analyze over thousands of event streams per second on a real time basis without latency, in order to be applicable to medical institution ERP systems.
목차
1. Introduction
2. Related Works
2.1. Big Data
2.2. Hadoop
2.3. CEP(Complex Event Processing)
2.4. Hadoop and CEP for Big Data Approach
2.5. Definitions and Characteristics of NoSQL
3. System Compositions and Designs
4. System Implementation
5. Conclusion
References