Practical Considerations for Real-Time Business Intelligence -- What Can Hierarchies Do for Data Streams? -- Leveraging Distributed Publish/Subscribe Systems for Scalable Stream Query Processing -- Transaction Reordering and Grouping for Continuous Data Loading -- A Scalable Heterogeneous Solution for Massive Data Collection and Database Loading -- Two-Phase Data Warehouse Optimized for Data Mining -- Document-Centric OLAP in the Schema-Chaos World -- Callisto: Mergers Without Pain -- Real-Time Acquisition of Buyer Behaviour Data – The Smart Shop Floor Scenario -- Business Process Learning for Real Time Enterprises -- An Integrated Approach to Process-Driven Business Performance Monitoring and Analysis for Real-Time Enterprises -- Quality Contracts for Real-Time Enterprises.

st The 1 Workshop on Business Intelligence for the Real-Time Enterprise (BIRTE nd 2006) was held on September 11, 2006 in conjunction with the 32 International Conference on Very Large Data Bases (VLDB 2006) in Seoul, Korea. The - location with VLDB is very important as the topic of the workshop was centered on different aspects in the lifecycle of business intelligence on very large enterprise-wide operational real-time data sets. In today’s competitive and highly dynamic environment, analyzing data to und- stand how the business is performing, to predict outcomes and trends, and to improve the effectiveness of business processes underlying business operations has become critical. The traditional approach to reporting is not longer adequate; users now - mand easy-to-use intelligent platforms and applications capable of analyzing real-time business data to provide insight and actionable information at the right time. The end goal is to improve the enterprise performance by better and timelier decision making, enabled by the availability of up-to-date, high-quality information.