An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Online association rule mining
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Mining time-changing data streams
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Processing complex aggregate queries over data streams
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Building the Operational Data Store
Building the Operational Data Store
Continuous queries over data streams
ACM SIGMOD Record
Realizing active data warehouses with off-the-shelf database technology
Software—Practice & Experience
Striving towards Near Real-Time Data Integration for Data Warehouses
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Approximate query processing using wavelets
The VLDB Journal — The International Journal on Very Large Data Bases
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
A Data-Warehouse/OLAP Framework for Scalable Telecommunication Tandem Traffic Analysis
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Load Shedding for Aggregation Queries over Data Streams
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Streaming queries over streaming data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Multi-dimensional regression analysis of time-series data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Dynamic interactive framework to link business intelligence with strategy
International Journal of Information Technology and Management
Traditional Business Intelligence vis-a-vis real-time Business Intelligence
International Journal of Information and Communication Technology
An Ontology-Based Autonomic System for Improving Data Warehouse Performances
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Implementing automated analyses in an active data warehouse environment using workflow technology
TEAA'06 Proceedings of the 2nd international conference on Trends in enterprise application architecture
About adopting event processing in manufacturing
ServiceWave'10 Proceedings of the 2010 international conference on Towards a service-based internet
From information to operations: Service quality and customer retention
ACM Transactions on Management Information Systems (TMIS)
International Journal of Strategic Information Technology and Applications
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The dynamic business environment of many organizations require massive monitoring of their processes in real-time in order to proactively respond to exceptional situations and to take advantage of time-sensitive business opportunities. The ability to sense and interpret events about a changing business environment requires an event-driven IT infrastructure for pwerforming fast and well-informed decisions and putting them into action. However, traditional Business Intelligence (BI) and Data Warehousing technologies do not directly address time sensitive monitoring and analytical requirements. We introduce an enhanced BI architecture that covers the complete process to sense, interpret, predict, automate and respond to business environments and thereby aims to decrease the reaction time needed for business decisions. We propose an event-driven IT infrastructure to operate BI applications which enable real-time analytics across corporate business processes, notifies the business of actionable recommendations or automatically triggers business operations, and effectively closing the gap between Business Intelligence systems and business processes. A scenario from the area of mobile phone fraud detection was chosen for building a prototype that illustrates the proposed approach by using current available IT technologies.