Process Data Store: A Real-Time Data Store for Monitoring Business Processes

With access to real-time information on critical performance indicators of business processes, managers and staff members can play a crucial role in improving the speed and effectiveness of an organization’s business operations. While the investments in data warehouse technologies have resulted in c...

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Bibliographic Details
Published inDatabase and Expert Systems Applications pp. 760 - 770
Main Authors Schiefer, Josef, List, Beate, Bruckner, Robert M.
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2003
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Business Process
Business Process Monitoring
Computer science; control theory; systems
Data Warehouse
Data Warehouse System
Enterprise Data Warehouse
Exact sciences and technology
Information systems. Data bases
Memory organisation. Data processing
Software
Access time
Surveillance
Decision support system
Decision making
Information processing
Firm management
Delay time
Reliability
Real time
Integrated management
Data warehouse
Monitoring
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Summary:With access to real-time information on critical performance indicators of business processes, managers and staff members can play a crucial role in improving the speed and effectiveness of an organization’s business operations. While the investments in data warehouse technologies have resulted in considerable information processing efficiencies for the organizations, there is still a significant delay in the time required for mission critical information to be delivered in a form that is usable to managers and staff. In this paper we introduce an architecture for business process monitoring based on a process data store which is a data foundation for operational and tactical decision-making by providing real-time access to critical process performance indicators to improve the speed and effectiveness of workflows. The process data store allows to identify and react to exceptions or unusual events that happened in workflows by sending out notifications or by directly changing the current state of the workflow. Our proposed architecture allows to transform and integrate workflow events with minimal latency providing the data context against which the event data is used or analyzed.
ISBN:9783540408062
3540408061
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-45227-0_74