Managing Continuous Data Integration Flows

Understanding the performance and dynamic behavior of workflow is crucial in being able to modify, maintain, and improve it. A particularly difficult aspect of measuring the performance of workflows is the dissemination of event data and its transformation into business metrics. In this paper we introduce an architecture that supports a continuous integration of event data from various source systems in near real-time into a data warehouse environment. The proposed architecture takes full advantage of existing J2EE (Java 2 Platform, Enterprise Edition) technology and uses an ETL container for the event data processing. We discuss the challenges of managing flows for continuously integrated data and show how a container environment can provide services that facilitate the flow management.

• Type: Conference
• Year: 2003
• Where: CAISE
• Authors: Josef Schiefer, Jun-Jang Jeng, Robert M. Bruckner
• Keywords: CAISE 2003, Data Warehouse Environment, Event Data, Event Data Processing