Concurrency in the Data Warehouse
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Business Intelligence in Healthcare Organizations
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Optimizing ETL Processes in Data Warehouses
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Data integration: the teenage years
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Real-time Performance Monitoring for an Enterprise Information Management System
ICEBE '08 Proceedings of the 2008 IEEE International Conference on e-Business Engineering
Data integration flows for business intelligence
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Just-In-Time Processing of Continuous Queries
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Information Value-Driven Near Real-Time Decision Support Systems
ICDCS '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems
ETL workflows: from formal specification to optimization
ADBIS'07 Proceedings of the 11th East European conference on Advances in databases and information systems
Data Load Distribution by Semi Real Time Data Warehouse
ICCNT '10 Proceedings of the 2010 Second International Conference on Computer and Network Technology
Applying data warehousing technique in pervasive assistive environment
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
Empowering data sources to manage clinical data
CBMS '10 Proceedings of the 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems
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In Data Warehouse (DW) environments, operational processes move data from sources to the warehouse. This includes data export, preparation, and loading usually performed using Extraction, Transformation and Loading (ETL) tools. Past research has treated DW "as collections of materialized views" whose data is regularly refreshed and locally stored [1]. Requirements have changed and real time transactions are required to support on-line operational decision making. Traditional DW systems may impose unacceptable delays due to their batch nature. ETL techniques are difficult to scale up to address the challenge of data loading, performance and low latency to provide real-time decision support. We propose a new approach for designing real-time DW in which traditional ETL does not apply. Data is pre-analysed by agents in each data source before being pushed as needed to the DW. The approach has been evaluated in a simulated environment and some of the results are discussed here.