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Business Intelligence: Concepts, Components, Techniques and Benefits

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Business Intelligence: Concepts, Components, Techniques and Benefits
Journal of Theoretical and Applied Information Technology
© 2005 - 2009 JATIT. All rights reserved. www.jatit.org

BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS, TECHNIQUES AND BENEFITS
JAYANTHI RANJAN Institute of Management Technology, Ghaziabad, Uttar Pradesh, India Email: jranjan@imt.edu

ABSTRACT For companies maintaining direct contact with large numbers of customers, however, a growing number channel-oriented applications (e.g. e-commerce support, call center support) create a new data management challenge: that is effective way of integrating enterprise applications in real time. To learn from the past and forecast the future, many companies are adopting Business Intelligence (BI) tools and systems. Companies have understood the importance of enforcing achievements of the goals defined by their business strategies through business intelligence concepts. It describes the insights on the role and requirement of real time BI by examining the business needs. The paper explores the concepts of BI, its components, emergence of BI, benefits of BI, factors influencing BI, technology requirements, designing and implementing business intelligence, and various BI techniques. 1. INTRODUCTION A specialized field of business intelligence known as competitive intelligence focuses solely on the external competitive environment. Information is gathered on the actions of competitors and decisions are made based on this information. Little if any attention is paid to gathering internal information. In modern businesses, increasing standards, automation, and technologies have led to vast amounts of data becoming available. Data warehouse technologies have set up repositories to store this data. Improved Extract, transform, load (ETL) and even recently Enterprise Application Integration tools have increased the speedy collecting of data. OLAP reporting technologies have allowed faster generation of new reports which analyze the data. Business intelligence has now become the



References: DOLAP-04, Washington, DC, USA. Retrieved May 17 2006 from www.acm.org Adelman Sid , Moss Larissa and Barbusinski Les. (2002) “I found several definitions of BI’, Inmon, W.H. (1999) ‘Building the Operational DM Review. Retrieved 17 August 2002 from Data Store’, Wiley Publishers-New York, 2nd edition. 69 Journal of Theoretical and Applied Information Technology © 2005 - 2009 JATIT. All rights reserved. www.jatit.org Malhotra, Y. (2000) ‘information management to knowledge management: Beyond “Hi-Tech Hidebound” systems’, in Srikantaiah, T. K. and Koenig, M.E.D. (Eds.) Knowledge Management, Medford, NJ. Nguyen Tho Manh, Schiefer Josef and Min Tjoa, A. (2005) ‘Data warehouse design 2: Sense & response service architecture (SARESA): an approach towards a real-time business intelligence solution and its use for a fraud detection application’, Proceedings of the 8th ACM international workshop on Data warehousing and OLAP, DOLAP '05, ACM Press. Stackowiak, R., Rayman, J. and Greenwald, R. (2007) ‘Oracle Data Warehousing and Business Intelligence Solutions’, Wiley Publishing, Inc, Indianapolis. Suefert Andhreas and Schiefer Josef. (2005) ‘Enhanced Business Intelligence- Supporting Business Processes with Real-Time Business Analytics’, Proceedings of the 16th international workshop on Database and Expert System applications-DEXA’05. Retrieved 19 June 2006 from www.ieee.org Tvrdikova, M. (2007), ‘Support of Decision Making by Business Intelligence Tools’, Computer Information Systems and Industrial Management Applications, 2007. CISIM '07. 6th International Conference, pp. 368. Zeng, L., Xu, L., Shi, Z., Wang, M. and Wu, W. (2007), ‘Techniques, process, and enterprise solutions of business intelligence’, 2006 IEEE Conference on Systems, Man, and Cybernetics October 8-11, 2006, Taipei, Taiwan, Vol. 6, pp. 4722. 70

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