Situational Business Intelligence.- On Solving Efficiently the View Selection Problem under Bag-Semantics.- QoS-Aware Publish-Subscribe Service for Real-Time Data Acquisition.- A Near Real-Time Reporting System for Enterprises Using JavaScript Instrumentation with Inter-colo Event Replication.- A Hybrid Row-Column OLTP Database Architecture for Operational Reporting.- The Reality of Real-Time Business Intelligence.- Beyond Conventional Data Warehousing - Massively Parallel Data Processing with Greenplum Database.- Scalable Data-Intensive Analytics.- Simplifying Information Integration: Object-Based Flow-of-Mappings Framework for Integration.

In todayís competitive and highly dynamic environment, analyzing data to understand how the business is performing, to predict outcomes and trends, and to improve the effectiveness of business processes underlying business operations has become cri- cal. The traditional approach to reporting is no longer adequate, users now demand easy-to-use intelligent platforms and applications capable of analyzing real-time bu- ness 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, - abled by the availability of up-to-date, high-quality information. As a response, the notion of "real-time enterprise" has emerged and is beginning to be recognized in the industry. Gartner defines it as "using up-to-date information, getting rid of delays, and using speed for competitive advantage is what the real-time enterprise is all about. . . Indeed, the goal of the real-time enterprise is to act on events as they happen. " Although there has been progress in this direction and many com- nies are introducing products toward making this vision a reality, there is still a long way to go. In particular, the whole lifecycle of business intelligence requires new techniques and methodologies capable of dealing with the new requirements imposed by the real-time enterprise.