• Document: A Five-Layered Business Intelligence Architecture
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IBIMA Publishing Communications of the IBIMA http://www.ibimapublishing.com/journals/CIBIMA/cibima.html Vol. 2011 (2011), Article ID 695619, 11 pages DOI: 10.5171/2011.695619 A Five-Layered Business Intelligence Architecture In Lih Ong1, Pei Hwa Siew1 and Siew Fan Wong2 1 Universiti Tunku Abdul Rahman, Selangor, Malaysia 2 Sunway University, Selangor, Malaysia ______________________________________________________________________________________________________________ Abstract Many organizations today have adopted business intelligence (BI) as a catalyst to meet specific business needs and to improve organizational effectiveness. Although BI has become more robust and pervasive, some organizations are still unable to maximize the return on their BI investments. One contributing reason is the lack of a good guiding BI architecture to support the implementation of such a system. Having a solid architecture can help organizations to better control the implementation process as well as the operation of the entire BI environment. A review of the existing literature shows that although the importance of a good BI architecture is non-arguable, research in this area is still lacking. To fill the gap, this paper proposes a framework of BI architecture which consists of five layers: data source, ETL, data warehouse, end user, and metadata layers. These five layers are essential to ensure high data quality and smooth information flow in a BI system. Keywords: business intelligence, BI architecture, framework, BI system ______________________________________________________________________________________________________________ Introduction marketplace (IBM, 2009). With more and more organizations becoming aware of the Business intelligence (BI) is “about how to value of BI, its market is expected to grow capture, access, understand, analyze and rapidly. According to Gartner (2011), the BI turn one of the most valuable assets of an market will grow 9.7 percent to reach enterprise - raw data - into actionable $10.8 billion in 2011. By 2014, this BI information in order to improve business market will reach $11.3 billion performance” (Azvine et al., 2005, p. 215). (MarketResearch.com, 2010) while the It pairs data gathering, data storage, and revenue for BI vendors will hit $7.7 billion knowledge management with analytic tools by 2012 (Sommer, 2008). to provide decision-makers with competitive information that often act as As organizations begin to adopt BI, one differentiators in today’s fierce business very important task is to make sure that environment (Negash, 2004). This explains they follow a good BI architectural plan in why BI has remained as the top technology their implementation process so as to priority for Chief Information Officers for ascertain the success of their BI the past five years (Gartner Research, investment. BI architecture is a framework 2006, 2007, 2008, 2009a, 2009b). detailing different components of BI (i.e., SpeciBically, a 2009 IBM Global Study of data, people, processes, technology, and the more than 2,500 CIOs found that 83 management) and how these components percent of respondents viewed BI as the need to come together to ensure smooth most important visionary element in functioning of a BI system (Rob & Coronel, enhancing their ability to compete in the 2007). Examples of information contained Copyright © 2011 In Lih Ong, Pei Hwa Siew and Siew Fan Wong. This is an open access article distributed under the Creative Commons Attribution License unported 3.0, which permits unrestricted use, distribution, and reproduction in any medium, provided that original work is properly cited. Contact author In Lih Ong E-mail: ongil1@mail2.utar.edu.my Communications of the IBIMA 2 in a BI architecture are the types of data applications, and BI portal. Nonetheless, that need to be collected, the methods to be one important component missing from used to analyze data, and the way to these existing BI architectures is that of present certain information. Having a solid analytical and reporting such as data BI architecture is critical. If the underlying mining, predictive analytics, and data architecture is not designed properly, visualization. These features are new BI inconsistencies that arise among the capabilities that are important and shoul

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