THE STUDYING OF CLOUD BUSINESS INTELLIGENCE SYSTEM ARCHITECTURE FOR ASEAN ECONOMIC COMMUNITY
Keywords:
Business Intelligence, Cloud Computing, System Architecture and ASEAN Economic CommunityAbstract
The private and public organizations in Thailand are preparing to deal with ASEAN Economic Community (AEC). Business Intelligence (BI) seems to be the important tools for driving the organizations. However, there is a variety of requirement and needs from executives’ perspectives to be addressed for business adaptation in terms of Business Intelligence adoption. Using BI for business analysis purpose is implementing tools and techniques for transform data into meaningful and useful information for business analysis purpose. Nevertheless, the organizations are facing the several problems such as managing of big data, complexity of system architecture’s design, high total cost of ownership, long-term maintenance, long-time deployment and lack of skillful IT people. Therefore, this leads to new initiatives about data center of business intelligence for AEC‘s member in order to support the business decision making and strengthen the competitive advantage including economic value added.
The purposes of this research are to; compare the system architecture’s design of business intelligence between on premise and on cloud services; propose the conceptual framework of 178 SUTHIPARITHAT Vol.30 No.93 January - March 2016 system architecture of infrastructure, platform and software for business intelligence; and also to study the technology factor for adoption of business intelligence. The qualitative method research was used in this study by using focus group with 12 experts who have skill and experience in information technology. The data analysis used content analysis technique to extract the knowledge from the experts.
The results of this study showed that the system architecture of business intelligence for AEC should adopt cloud service provider for infrastructure, platform and software. In addition, the fee should be charged per usage. Furthermore, the technology adoption of business intelligence are 1) Building user empowerment, 2) Total cost of ownership and time for deployment, 3) Security, 4) Readiness of IT resources, 5) Extraction-Transformation-Loading for Data. In summary, this research reflects the feasibility study for technical aspect of business intelligence on cloud for AEC.
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