Emerging Business Intelligence Technologies for SMEs

Emerging Business Intelligence Technologies for SMEs

Jorge Bernardino (Institute Polytechnic of Coimbra – ISEC, Portugal)
ISSN: 2327-3275|EISSN: 2327-3283|ISBN13: 9781466643734|ISBN10: 1466643730|EISBN13: 9781466643741
DOI: 10.4018/978-1-4666-4373-4.ch001
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MLA

Bernardino, Jorge. "Emerging Business Intelligence Technologies for SMEs." Handbook of Research on Enterprise 2.0: Technological, Social, and Organizational Dimensions. IGI Global, 2014. 1-28. Web. 27 Mar. 2020. doi:10.4018/978-1-4666-4373-4.ch001

APA

Bernardino, J. (2014). Emerging Business Intelligence Technologies for SMEs. In M. Cruz-Cunha, F. Moreira, & J. Varajão (Eds.), Handbook of Research on Enterprise 2.0: Technological, Social, and Organizational Dimensions (pp. 1-28). Hershey, PA: IGI Global. doi:10.4018/978-1-4666-4373-4.ch001

Chicago

Bernardino, Jorge. "Emerging Business Intelligence Technologies for SMEs." In Handbook of Research on Enterprise 2.0: Technological, Social, and Organizational Dimensions, ed. Maria Manuela Cruz-Cunha, Fernando Moreira and João Varajão, 1-28 (2014), accessed March 27, 2020. doi:10.4018/978-1-4666-4373-4.ch001

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Abstract

Small and Medium-Sized Enterprises (SMEs) are socially and economically important, since they represent 98% of all enterprises, providing around 90 million jobs in the European Union, and contribute to entrepreneurship and innovation. However, SMEs face particular difficulties in order to be competitive in a global world. In recent time, technology applications in different fields, especially Business Intelligence (BI) have been developed rapidly and considered to be one of the most significant uses of information technology. BI is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. This represents a tremendous competitive advantage that allows achieving and exploring the collective intelligence of the organization, enabling contextual, agile, and simplified information exchange and collaboration among distributed workforce and networks of partners and customers, which can be defined as Enterprise 2.0. Despite these advantages, the companies applying such systems may also encounter problems in decision-making processes because of the highly diversified interactions within the systems. Hence, the choice of a suitable BI platform for SMEs is important to take the great advantage of using information technology in all organizational fields. The authors analyze seven open source Business Intelligence tools, free of charge, given that one of the main objectives is to reduce costs and enhance Enterprise 2.0 using new open source technologies.

References

Actuate/BIRT. (2011). BIRT open source. Retrieved from http://www.actuate.com/
Anderson-Lehman R. Watson H. J. Wixom B. H. Hoffer J. A. (2004). Continental airlines flies high with real-time business intelligence.MIS Quarterly Executive, 3(4), 163–176.
Bergeron B. (2000). Regional business intelligence: The view from Canada.Journal of Information Science, 26(3), 153–160. 10.1177/016555150002600305
Bernardino J. Ribeiro P. (2011). Open source business intelligence: An alternative to proprietary tools.International Journal of Electronic Business, 9(3), 219–237. 10.1504/IJEB.2011.042543
Beyer, M. (2009a, February). Tutorial: Key roles for successful BI/DW delivery: Business intelligence solution architect. Gartner.
Beyer, M. (2009b, April). Fundamentals of data warehousing for the CIO. Gartner.
Bhagwat R. Sharma M. K. (2006). Management of information system in Indian SMEs: An exploratory study.International Journal of Enterprise Network Management, 1(1), 99–125. 10.1504/IJENM.2006.010068
Bucher T. Gericke A. Sigg S. (2009). Process-centric business intelligence.Business Process Management Journal, 15(3), 408. 10.1108/14637150910960648
Cai H. Reinwald B. Wang N. Guo C. (2011). SaaS multi-tenancy: Framework, technology, and case study.International Journal of Cloud Applications and Computing, 1(1), 62–77. 10.4018/ijcac.2011010105
Chaudhary S. (2004). Management factors for strategic BI success. In Business intelligence in digital economy: Opportunities, limitations and risks. Hershey, PA: IDEA Group Publishing.
Chaudhary S. Dayal U. Narasayya V. (2011). An overview of business intelligence technology.Communications of the ACM, 54(8), 88–98. 10.1145/1978542.1978562
Chen L. Soliman K. S. Mao E. Frolick M. N. (2000). Measuring user satisfaction with data warehouses: An exploratory study.Information & Management, 103–110. 10.1016/S0378-7206(99)00042-7
Corbett P. Ward D. (2006). Open source reporting solutions for institutional reporting: The BIRT approach. Australasian Association for Institutional Research. AAIR.
Cossentino, M. (2007). Open source software. Retrieved from http://www.pa.icar.cnr.it/cossentino/ICT/ppt/S11%20-%20Open%20Source%20Software.pdf
Cusumano M. (2010). Cloud computing and SaaS as new computing platforms.Communications of the ACM, 53(4), 27–28. 10.1145/1721654.1721667
Damiani, E., Frati, F., & Monteverdi, C. (2009). Open source BI adoption. Retrieved from http://www.ow2.org/xwiki/bin/download/BusinessIntelligence/Documents/OSBIadoption-v10.pdf
Devlin B. P. Murphy P. T. (1988). An architecture for a business and information system.IBM Systems Journal, 7(1), 60–80. 10.1147/sj.271.0060
Dholakia R. R. Kshetri N. (2004). Factors impacting the adoption of the Internet among SMEs.Small Business Economics, 23(4), 311–322. 10.1023/B:SBEJ.0000032036.90353.1f
Eclipse/BIRT. (2011). BIRT project. Retrieved from http://www.eclipse.org/birt
Embarcadero Technologies. (2008). Why data warehouse projects fail. Retrieved from http://www.embarcadero.com/resources/technical_papers/Why-Data-Warehouse-Projects-Fail.pdf
European Union. (2003). The new SME definition: User guide and model declaration. Official Journal of the European Union, 124, 36.
Evelson B. Hammond J. S. (2010). The Forrester Wave™: Open source business intelligence (BI), Q3 2010. Forrester Research.
Gonzales M. L. Wells D. L. (2006). BI strategy: How to create and document. Austin, TX: HandsOn-BI, LLC.
Grabova O. Darmont J. Chauchat J.-H. Zolotaryova I. (2010). Business intelligence for small and middle-sized entreprises.SIGMOD Record, 39(2), 39–50. 10.1145/1893173.1893180
Hwang H.-G. Ku C.-Y. Yen D. V. Cheng C.-C. (2004). Critical factors influencing the adoption of data warehouse technology: A study of the banking industry in Taiwan.Decision Support Systems, 37(1), 1–21. 10.1016/S0167-9236(02)00191-4
IBM. (2009). The new voice of the CIO. Retrieved from http://www-935.ibm.com/services/us/cio/ciostudy/
Inmon B. (2002). Building the data warehouse (3rd ed.). New York: Wiley and Sons.
Jasperforge. (2011). Jasperforge. Retrieved from http://jasperforge.org/
Jaspersoft. (2011). Jaspersoft. Retrieved from http://www.jedox.com/
Jordan J. Ellen C. (2009). Business need, data and business intelligence.Journal of Digital Asset Management, 5(1). 10.1057/dam.2008.53
Joshi K. Curtis M. (1999). Issues in building a successful data warehouse.Information Strategy: The Executive's Journal, 15(2), 28–35.
Kelly, S. (1997). Data marts: The latest silver bullet. Data Mart Review, 12-16.
Kimball R. Ross M. (2002). The data warehouse toolkit: The complete guide to dimensional modeling (2nd ed.). New York: John Wiley and Sons.
Knight, M. (2011). BI growth to buck economic trends. Retrieved July 14, 2011, from http://www.itpro.co.uk/183480/bi-growth-to-buckeconomic-trends
Koch, C. (2003). Open source - Your open source plan. Retrieved from http://www.cio.com/article/31768/Open_Source_Your_Opensource_Plan
Lawton G. (2009). Users take a close look at visual analytics.IEEE Computer, 42(2), 19–22. 10.1109/MC.2009.61
Lefebvre L. Harvey J. Lefebvre E. (1991). Technological experience and the technology adoption decisions in small manufacturing firms.R & D Management, 21(3), 241–249. 10.1111/j.1467-9310.1991.tb00761.x
Lerner J. Tirole J. (2002). Some simple economics of open source.The Journal of Industrial Economics, 50(2), 197–234. 10.1111/1467-6451.00174
Levy M. Powell P. (1998). SME flexibility and the role of information systems.Small Business Economics, 11(2), 183–196. 10.1023/A:1007912714741
Levy M. Powell P. Yetton P. (2002). The dynamics of SME information systems.Small Business Economics, 19(4), 341–354. 10.1023/A:1019654030019
Lybaert N. (1998). The information use in a SME: Its importance and some elements of influence.Small Business Economics, 10(2), 171–191. 10.1023/A:1007967721235
Mehrtens J. Cragg P. B. Mills A. M. (2001). A model of internet adoption by SMEs.Information & Management, 39(3), 165–176. 10.1016/S0378-7206(01)00086-6
Mimno, P. (2002). How to avoid data mart chaos using hybrid methodology. TDWI Flash point column.
Mullins, R., Duan, Y., Hamblin, D., Burrell, P., Jin, H., Jerzy, G., … Aleksander, B. (2007). A web based intelligent training system for SMEs. The Electronic Journal of e-Learning, 5, 39-48.
Olszak C. M. Ziemba E. (2006). Business intelligence systems in the holistic infrastructure development supporting decision-making in organizations. Interdisciplinary Journal of Information. Knowledge and Management, 1, 47–58.
Open, I. (2011). Open intelligence. Retrieved from http://www.openi.org/
OpenSourceInitiative. (2011). Retrieved from http://www.opensource.org/
Pentaho. (2011). Pentaho open source BI. Retrieved from http://www.pentaho.com/
Pentaho Community. (2011). Pentaho community home. Retrieved from http://community.pentaho.com/
Power, D. J. (2007). A brief history of decision support systems, version 4.0. DSSResources.com. Retrieved from http://DSSResources.COM/history/dsshistory.html
Rist R. (1997). Challenges faced by the data warehousing pioneers.Journal of Data Warehousing, 2(1).
Rudra, A., & Yeo, E. (1999). Key issues in achieving data quality and consistency in data warehousing among large organizations in Australia. In Proceedings of the 32nd Hawaii International Conference on System Sciences, (pp. 7012-7019). IEEE.
Snowden D. Boone M. (2007). A leader's framework for decision making.Harvard Business Review, 85(11), 68–76.18159787
Spago, B. I. (2011). Spago business intelligence. Retrieved from http://www.spagoworld.org/
Spruit M. Abdat N. (2012). The pricing strategy guideline framework for SaaS vendors.International Journal of Strategic Information Technology and Applications, 3(1), 38–53. 10.4018/jsita.2012010103
Strange K. F. T. (2009). Making BI and data warehousing strategic: The key issues, LE-19-4691. Gartner Group.
Themistocleous M. Chen H. (2004). Investigating the integration of SMEs' information systems: An exploratory case study.International Journal of Information Technology and Management, 3(2-4), 208–234. 10.1504/IJITM.2004.005033
Turban, E. Aronson, Liang, & Sharda, R. (2007). Decision support and business intelligence systems (8th Ed.). Englewood Cliffs, NJ: Prentice Hall.
Turban E. King D. Lee J. K. Viehland D. (2004). Electronic commerce 2004: A managerial perspective (3rd ed.). Englewood Cliffs, NJ: Prentice Hall.
Turban E. Sharda S. Aronson J. E. King D. (2008). Business intelligence: A managerial approach. Upper Saddle River, NJ: Pearson Prentice Hall.
Vanilla. (2011). True open source BI platform. Retrieved from http://www.bpm-conseil.com/
Varner, P. E. (1999). The economics of open source software. Retrieved from http://www.cs.virginia.edu/~pev5b/writing/econ_oss/
Watson H. J. (2009). Tutorial: Business intelligence –Past, present, and future.Communications of the Association for Information Systems, 25(39).
Watson H. J. Gerard J. G. Gonzalez L. E. Haywood M. E. Fenton D. (1999). Data warehousing failures: Case studies and findings.Journal of Data Warehousing, 44–55.
Watson H. J. Wixom B. H. (2007). The current state of business intelligence.IEEE Computer, 40(9), 96–99. 10.1109/MC.2007.331
Wixom B. Watson H. J. (2001). An empirical investigation of the factors affecting data warehousing success.Management Information Systems Quarterly, 25(1), 17–41. 10.2307/3250957
Xie, G., Yang, Y., Liu, S., Qiu, Z., Pan, Y., & Zhou, X. (2007). EIAW: Towards a business-friendly data warehouse using semantic web technologies. In K. Aberer, et al. (Eds.), ISWC/ASWC ’07: Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (LNCS), (vol. 4825, pp. 851-904). Berlin: Springer Verlag.

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