Incorporating Data Stream Analysis into Decision Support Systems

Incorporating Data Stream Analysis into Decision Support Systems

Damianos Chatziantoniou (Athens University of Economics and Business, Greece) and George Doukidis (Athens University of Economics and Business, Greece)
DOI: 10.4018/978-1-59140-553-5.ch252
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Abstract

Traditional decision support systems (DSS) and executive information systems (EIS) gather and present information from several sources for business purposes. It is an information technology to help the knowledge worker (executive, manager, analyst) make faster and better decisions. So far, this data was stored statically and persistently in a database, typically in a data warehouse. Data warehouses collect masses of operational data, allowing analysts to extract information by issuing decision support queries on the otherwise discarded data. In a typical scenario, an organization stores a detailed record of its operations in a database, which is then analyzed to improve efficiency, detect sales opportunities, and so on. Performing complex analysis on this data is an essential component of these organizations’ businesses. Chaudhuri and Dayal (1997), present an excellent survey on decision-making and on-line analytical processing (OLAP) technologies for traditional database systems.

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