Cooperative Business Intelligence Model Using a Multiagent Platform

Modern companies wish to utilize business intelligence (BI) to track and analyze their courses of action. Many BI applications serve this purpose at many levels, starting from documenting and charting and ending with analytics and decision support systems, which are considered a sufficient complemen...

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Bibliographic Details
Published in:Scientific programming 2020, Vol.2020 (2020), p.1-12
Main Authors: Khozium, Mohamed O., Farooqi, Norah S.
Format: Article
Language:English
Subjects:
Algorithms
Business
Business intelligence software
Case studies
Consultancy services
Cooperation
Decision analysis
Decision making
Decision support systems
Feasibility studies
Information management
Intelligence (information)
Knowledge
Multiagent systems
Resource management
Success
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Summary:Modern companies wish to utilize business intelligence (BI) to track and analyze their courses of action. Many BI applications serve this purpose at many levels, starting from documenting and charting and ending with analytics and decision support systems, which are considered a sufficient complement to consultancy and management resources. However, the contemporaneous BI software is missing two functionalities. First, although nearly all applications of the same genre use almost identical concepts, there is no unified application programming interface (API) to enable interaction. The second problem is a consequence of the first issue. Without a unified API, BI applications cannot be integrated, eliminating any possibility of establishing universal platforms for BI distributed services. Lacking these two functionalities makes developers reinvent the wheel with each new implementation. To solve these problems, we propose a platform running a multiagent business intelligence system. This system empowers the available BI resources to serve a larger segment of the BI end-user applications cooperatively. To build this system, we propose a unified model that enables distributive agent-based tasking and cooperative interaction. This allows researchers to cooperate in spreading the multiagent platform’s functionality and helps them proceed toward more detailed analysis considering agents’ construction. Moreover, it will enable BI service providers to cooperatively implement new applications and develop better solutions while maintaining a functional end-user program.
ISSN:1058-9244
1875-919X
DOI:10.1155/2020/8898719