BUSINESS INTELLIGENCE - State of the Art, Trends, and Open Issues

Ana Azevedo, Manuel Filipe Santos

Abstract

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years the evolution in this area has been considerable. An overview of some aspects of the area is presented in this article. The roots of BI and its usual associations with Knowledge Management Systems (KMS), Competitive Intelligence (CI), and Artificial Intelligence (AI) are introduced. From the literature review, it was observed that the definition of an underlying structure on the area is missing. Therefore, a framework for BI is defined. The state of the art of BI research field was made, presenting recent trends and open issues for research.

References

  1. Alavi, M. & Leidner, D.E. (2001). Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly, 25, 107-136.
  2. Arnott, D. & Pervan, G. (2008). Eigth Key Issues for the Decision Support Systems Discipline. Decision Support Systems, 44, 657-672.
  3. Brobst, S. & Pareek, A. (2009). New Trends in Data Acquisition Services for the Real-Time Enterprise. Business Intelligence Journal, 14, 52-58.
  4. Cheng, H., Lu, Y. & Sheu, C. (2009). An Ontology-Based Business Intelligence Application In A Financial Knowledge Management System. Expert Systems with Applications, 36, 3614-3622.
  5. Clark, T. D., Jones, M. C. & Armstrong, C.P. (2007). The Dynamic Structure of Management Support Systems: Theory Development, Research, Focus, and Direction. MIS Quarterly, 31, 579-615.
  6. Eckerson, W. W. (2008). Q&A: Pervasive Business Intelligence. Business Intelligence Journal, 13, 48-50.
  7. Eckerson, W. W. (2009). Research Q&A: Performance Management Strategies. Business Intelligence Journal, 14, 24-27.
  8. Elbashir, M. Z., Collier, P. A. & Davern, M.J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International Journal of Accounting Information Systems, 9, 135-153.
  9. Fayyad, U. M., Piatetski-Shapiro, G. & Smyth, P. (1996). From data mining to knowledge discovery: an overview. In U. M. Fayyad, G. Piatetski-Shapiro, P. Smyth & R. Uthurusamy (Eds.), Advances in knowledge discovery and data mining. 1, 1-34. AAAI Press / The MIT Press.
  10. Golfarelli, M., Rizzi, S. & Cella, I. (2004). Beyond Data Warehousing: Whats Next in Business Intelligence. In DOLAP04.1-6.
  11. Hannula, M. & Pirttimäki, V. (2003). Business Intelligence Empirical Study on the Top 50 Finnish Companies. Journal of American Academy of Business, 2, 593-599.
  12. Hobek, R., Ariyachandra, T. & Frolick, M.N. (2009). The Importance of Soft Skills in Business Intelligence Implementations. Business Intelligence Journal, 14, 28-36.
  13. Hoffman, T. (2009). 9 Hottest Skills for 7809. Computer World, January 1, 26-27.
  14. Klawans, B. (2008). Embedded or Conventional BI: Determining the Right Combination of BI for Your Business. Business Intelligence Journal, 13, 30-36.
  15. Kudyba, S. & Hoptroff, R. (2001). Data Mining and Business Intelligence: a Guide to Productivity. Idea Group Publishing.
  16. Li, S., Shue, L. & Lee, S. (2008). Business Intelligence Approach to Supporting Strategy-making of ISP Service Management. Expert Systems with Applications, 35, 739-754.
  17. Liebowitz, J. (2006). Strategic Intelligence: Business Intelligence, Competitive Intelligence, and Knowledge Management. Auerbach Publications.
  18. Lin, Y., Tsai, K., Shiang, W., kuo, T. & Tsai, C. (2009). Research on using ANP to establish a performance assessment model for business intelligence systems. Expert Systems with Applications, 36, 4135-4146.
  19. Lunger, K. (2008). Debunking Three Myths of Pervasive Business Intelligence: How to Create a Truly Democratic BI Environment. Business Intelligence Journal, 13, 38-41.
  20. Lunh, H. P. (1958). A Business Intelligence System. IBM Journal of Research and Development, 2, 314-319.
  21. March, S. T. & Hevner, A.R. (2007). Integrated decision support systems: A data warehousing perspective. Decision Support Systems, 43, 1031-1043.
  22. Michalewicz, Z., Schmidt, M., Michalewicz, M. & Chiriac, C. (2007). Adaptive Business Intelligence. Springer.
  23. Moss, L. T. & Shaku, A. (2003). Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. Pearson Education.
  24. Negash, S. (2004). Business Intelligence. Comunication of the Association for Information Systems, 13, 177-195.
  25. Nemati, H. R., Steiger, D. M., Iyer, L. S. & Herschel, R.T. (2002). Knowledge Warehouse: an Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing. Decision Support Systems, 33, 143-161.
  26. Pervan, G. & Arnott, D. (2006). Research in Data Warehousing and Business Intelligence: 1990-2004. In Proceedings of CIDMDS2006..
  27. Power, D. J. (2007). A Brief History of Decision Support System. DSSResources.COM, Version 4.0, World Wide Web, http://dssresources.com/history/dsshistory.html,March 10.
  28. Raisinghani, M. (2004). Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks. Idea Group Publishing.
  29. Richardson, J., Schlegel, K. & Hostmann, B. (2009). Magic Quadrant for Business Intelligence Platforms.
  30. Richardson, J., Schlegel, K., Hostmann, B. & McMurchy, N. (2008). Magic Quadrant for Business Intelligence Platforms, 2008.
  31. Shim, J. P., Warkentin, M., Courtney, J. F., Power, D. J., Sharda, R. & Carlsson, C. (2002). Past, Present, and Future of Decision Support Technology. Decision Support Systems, 32, 111-126.
  32. Strenger, L. (2008). Coping with "Big Data" Growing Pains. Business Intelligence Journal, 13, 45-52.
  33. Thierauf, R. J. (2001). Effective Business Intelligence Systems. Quorum Books.
  34. Turban, E., Aroson, J. E., Liang, T. & Sharda, R. (2007). Decision Support and Business Intelligence Systems. Pearson Prentice Hall.
  35. Turban, E., Sharda, R., Aroson, J. E. & King, D. (2008). Business Intelligence: A Managerial Approach. Pearson Prentice Hall.
  36. Watson, H. J. (2009). Bridging the IT/Business Culture Chasm. Business Intelligence Journal, 14, 4-7.
  37. Wormus, T. (2008). Complex Event Processing: Analytics and Complex Event Processing: Adding Intelligence to the Event Chain. Business Intelligence Journal, 13, 53-58.
  38. Zeller, J. (2007). Business Intelligence: The Chicken or the Egg. BI Review Magazine, May 8, 2007, http://www.informationmanagement.com/bissues/20070601/2600340-1.html.
  39. Zeller, J. (2008). Business Intelligence: the Road Trip. Information Management Special Reports, December 2, 2008.
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Paper Citation


in Harvard Style

Azevedo A. and Filipe Santos M. (2009). BUSINESS INTELLIGENCE - State of the Art, Trends, and Open Issues . In Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2009) ISBN 978-989-674-013-9, pages 296-300. DOI: 10.5220/0002303602960300


in Bibtex Style

@conference{kmis09,
author={Ana Azevedo and Manuel Filipe Santos},
title={BUSINESS INTELLIGENCE - State of the Art, Trends, and Open Issues},
booktitle={Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2009)},
year={2009},
pages={296-300},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002303602960300},
isbn={978-989-674-013-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Management and Information Sharing - Volume 1: KMIS, (IC3K 2009)
TI - BUSINESS INTELLIGENCE - State of the Art, Trends, and Open Issues
SN - 978-989-674-013-9
AU - Azevedo A.
AU - Filipe Santos M.
PY - 2009
SP - 296
EP - 300
DO - 10.5220/0002303602960300