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Information technology tools for Business Intelligence development in organizations

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Warianty tytułu
PL
Narzędzia technologii informacyjnej w rozwoju Business Intelligence w organizacjach
Języki publikacji
EN
Abstrakty
EN
The research objective for this study is to investigate different Information Technology (IT) tools for Business Intelligence (BI) development. Firstly, the issue of BI was identified and the various ages in BI development were presented. Then, the most important IT tools used in BI development were discussed. Finally, some strengths and weaknesses of described tools were demonstrated. The study was based mainly on a critical analysis of literature, creative thinking and an interpretive philosophy. The results of this research can be used by IT and business leaders as they plan and develop BI applications in their organizations.
PL
Celem artykułu jest rozpoznanie możliwości różnych narzędzi IT do budowy aplikacji Business Intelligence (BI). Na wstępie zidentyfikowano istotę BI oraz opisano trzy etapy rozwoju systemów BI. Następnie omówiono różne narzędzia IT, jakie mogą być stosowane do budowy BI w organizacjach. Ostatecznie, mocne i słabe strony tych narzędzi zostały zaprezentowane. Badania zostały przeprowadzone w oparciu o krytyczną analizę literatury przedmiotu. Wyniki badań mogą być interesujące dla specjalistów IT oraz menedżerów, którzy planują tworzenie aplikacji BI w swoich organizacjach.
Rocznik
Strony
132--142
Opis fizyczny
Bibliogr. 34 poz., tab.
Twórcy
autor
  • University of Economics in Katowice
autor
  • University of Louisville, USA
Bibliografia
  • 1. Borgatti S.P., Everet M.G., Freeman L.C., 2002, UCInet for Widows: Software for Social Network Analysis, Harvard, MA Analytic Technologies.
  • 2. Capgemini, 2013, Consulting. Technology. Outsourcing, http://www.capgemini.com/sites/default/files/resource/pdf/Search-Based_BI.pdf, Access on: 18.09.2013.
  • 3. Chaudhary S., 2014, Management factors for strategic BI success, [in:] M.S. Raisinghani (Eds.), Business Intelligence in digital economy. Opportunities, limitations and risks, IGI Global, Hershey.
  • 4. Chen H., Chiang R.H.L., Storey V.C., 2012, Business Intelligence and analytics: from Big data to big impact, “MIS Quarterly”, 36(4).
  • 5. Clavier P.R., Lotriet H., Loggerenberger J., 2012, Business Intelligence Challenges in the Context of Goods-and Service-Domain Logic, [in:] Proceedings of the 45 Hawaii International Conference on System Science, IEEE Computer Society.
  • 6. Conn S.S., 2015, OLTP and OLAP Data Integration: A Review of Feasible Implementation Methods and Architectures for Real Time Data Analysis, http://academic.regis.edu/cias/Library/pid54211.pdf, Access on: 15.02.2015.
  • 7. Cook R., 2015, In Memory Databases For BI Applications and ERP, http://it.toolbox.com/blogs/inside-erp/in-memory-databases-for-bi-applications-and-erp-61150, Access on: 20.02.2015.
  • 8. Davenport T.H., Harris J.G., 2007, Competing on Analytics, The New Science on Winning, Harvard Business School, Press Boston Massachusetts.
  • 9. Davenport T. H., Harris J. G., Morison R., 2010, Analytics at Work: Smarter Decisions, Better Results, Cambridge, Harvard Business Press.
  • 10. Hannula M., Pirttimaki V., 2003, Business intelligence empirical study on the top 50 Finnish companies, “Journal of American Academy of Business”, 2(2).
  • 11. Isik O., Jones M. C., Sidorova A., 2011, Business Intelligence (BI) Success and the Role of BI Capabilitie, “Intelligent Systems in Accounting, Finance and Management”, 18.
  • 12. Kirtland A., 2006, Executive Dashboard, http://DSSResources.com, Access on: 10.02.2006.
  • 13. Larose D.T., 2005, Discovering Knowledge in Data. An Introduction to data Mining, New York, John Wiley & Sons, Inc.
  • 14. Larson B., 2008, Delivering Business Intelligence with Microsoft SQL Server 2008, New York, McGraw-Hill Osborne Media.
  • 15. Meyer S.R., 2001, Which ETL Tool is Right for You?, “DM Review Magazine“, June 1.
  • 16. Moss L., Atre S., 2003, Business Intelligence Roadmap: The Complete Lifecycle for Decision-Support Applications, Boston, Addison-Wesley.
  • 17. Negash S., Gray P., 2008, Business Intelligence, [in:] F. Burstein and C.W Holsapple (Eds.), Decision Support Systems, Berlin, Springer.
  • 18. Newman M.E.J., 2010, Networks. An Introduction, Oxford, Oxford University Press.
  • 19. Olszak C.M., 2014a, An overview of information tools and technologies for competitive intelligence building. Theoretical approach, “Issues in Informing Science and Information Technology”, 11.
  • 20. Olszak C.M., 2014b, Business Intelligence and Analytics in Organizations, [in:] M. Mach-Król, C.M. Olszak, T. Pełech-Pelichowski (Eds.), Advanced in ICT for Business, Industry and Public Sector, London, Springer.
  • 21. Olszak C.M, 2014c, Business Intelligence in cloud, “Polish Journal of Management Studies”, 10(2).
  • 22. Olszak C.M., 2015, Towards better understanding and using of Business Intelligence in organizations, “Information Systems Management” (in print).
  • 23. Poul S., Gautman N., Balint R., 2003, Preparing and data mining with Microsoft SQL Server 2000 and Analysis Services, New York, Addison-Wesley.
  • 24. Riad A.M., Hassan Q.F.,2008, Service-Oriented Architecture – A New Alternative to Traditional Integration Methods in B2B Applications, “Journal of Convergence Information Technologies”.
  • 25. Robins G., Pattison P., Kalish Y., Lusher D., 2007, An Introduction to Exponential Random Graph (p*) Models for Social Networks, “Social Networks”, 29(2).
  • 26. Sahay B.S., Ranjan J., 2008, Real time business intelligence in supply chain analytics, „Information Management & Computer Security“, 16(1).
  • 27. SAS, 2013, https://www.sas.com/technologies/bi/visualization, Access on: 15.09.2013.
  • 28. Schick A., Frolick M., Ariyachandra T., 2011, Competing with BI and Analytics at Monster Worldwide, [in:] Proceedings of the 44 Hawaii International Conference on System Sciences, Hawaii.
  • 29. Tan P.N., Steinbach M., Kumar V., 2005, Introduction do Data Mining, New York, Addison-Wesley.
  • 30. Vasiliu A., 2009, Dashboards and scorecards: linking Management Reporting to Execution, http://DSSResourcess.com, Access on: 10.02.2009.
  • 31. Veber J. 2012, Operational-economic aspects of cloud computing, [in:] M. Tvrdikova, J. Minster and P. Rozenhal (Eds.), IT for Practice, Ostrava, VSB-TU Economicka Faculta.
  • 32. Vercellis C., 2009, Business Intelligence, Chichester, Wiley.
  • 33. Witten I.H., Frank E., Hall M., 2011, Data Mining: Practical Machine Learning Tools and Techniques, San Francisco, Morgan Kaufland.
  • 34. Wixom B.H., Watson H.J., Werner T., 2011, Developing an Enterprise Business Intelligence Capability: The Norfolk Southern Journey, “MIS Quarterly Executive”, 10(2).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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