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On the model design of integrated intelligent big data analytics systems

Kun Chen (Department of Financial Mathematics and Engineering, South University of Science and Technology, Shenzhen, China)
Xin Li (Department of Information Systems, City University of Hong Kong, Kowloon, Hong Kong, China)
Huaiqing Wang (Department of Financial Mathematics and Engineering, South University of Science and Technology, Shenzhen, Guangdong, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 19 October 2015

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Abstract

Purpose

Although big data analytics has reaped great business rewards, big data system design and integration still face challenges resulting from the demanding environment, including challenges involving variety, uncertainty, and complexity. These characteristics in big data systems demand flexible and agile integration architectures. Furthermore, a formal model is needed to support design and verification. The purpose of this paper is to resolve the two problems with a collective intelligence (CI) model.

Design/methodology/approach

In the conceptual CI framework as proposed by Schut (2010), a CI design should be comprised of a general model, which has formal form for verification and validation, and also a specific model, which is an implementable system architecture. After analyzing the requirements of system integration in big data environments, the authors apply the CI framework to resolve the integration problem. In the model instantiation, the authors use multi-agent paradigm as the specific model, and the hierarchical colored Petri Net (PN) as the general model.

Findings

First, multi-agent paradigm is a good implementation for reuse and integration of big data analytics modules in an agile and loosely coupled method. Second, the PN models provide effective simulation results in the system design period. It gives advice on business process design and workload balance control. Third, the CI framework provides an incrementally build and deployed method for system integration. It is especially suitable to the dynamic data analytics environment. These findings have both theoretical and managerial implications.

Originality/value

In this paper, the authors propose a CI framework, which includes both practical architectures and theoretical foundations, to solve the system integration problem in big data environment. It provides a new point of view to dynamically integrate large-scale modules in an organization. This paper also has practical suggestions for Chief Technical Officers, who want to employ big data technologies in their companies.

Keywords

Acknowledgements

This paper was supported by GRF grant (CityU 149412) from the Hong Kong Government, SUSTC Fundamental Research Grant (FRG-SUSTC1501A-20), and the Shenzhen Research Grant (No. JCYJ2010417105742712).

Citation

Chen, K., Li, X. and Wang, H. (2015), "On the model design of integrated intelligent big data analytics systems", Industrial Management & Data Systems, Vol. 115 No. 9, pp. 1666-1682. https://doi.org/10.1108/IMDS-03-2015-0086

Publisher

:

Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited

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