This thesis focuses on the area of data management and creates a framework to monitor data from a variety of data sources in real time using data warehouses. This research proposes a new way to design a monitoring infrastructure that empowers the use of local knowledge and distributes the data analysis in architectures that uses a data warehouse, the development of a prototype was needed to demonstrate the validity of the design. The findings of this research show that by monitoring key behaviours in the data at the source level, evaluating them and then responding only to data abnormalities, the proposed architecture is able to respond and/or alert to unusual scenarios in a more effective and efficient way than traditional right time data warehousing strategies.
Year Manuscript Completed
Computer Science (0984)
Data analysis; Data management; Architecture Data processing.
Primary Language of Manuscript
Recommended CitationEmma Chavez-Mora (January 2013) Using Local Intelligence to Actively Monitor Distributed Data Sources in Decision Making Architectures, PhD, ePublications@bond, School of Information Technology.
01Front.pdf (117 kB)