Analiza i ocena dorobku naukowego z zakresu Business Intelligence - wybrane zagadnienia

• Autorzy: Celina M. Olszak

Warianty tytułu

The Analysis and Evaluation of Scientific Achievements in Business Intelligence - Selected Issues

• Języki publikacji: PL

Abstrakty

Celem opracowania jest dokonanie wstępnego przeglądu i oceny wybranych teorii naukowych dotyczących rozwoju systemów BI oraz wskazanie rekomendacji i dalszych kierunków badawczych w tym zakresie. Do realizacja tak postawionego celu badawczego wykorzystano przede wszystkim metodę analizy bibliograficznej, metody deskrypcyjne I dedukcyjne oraz metodę syntezy. W pierwszej kolejności zwrócono uwagę na trudności w interpretacji terminu BI, następnie słabym powiązaniu tematyki BI z teoriami naukowymi, a w konsekwencji brakiem propozycji konceptualnego modelu BI oraz niewystarczająco rozwiniętymi modelami dojrzałości BI. (fragment tekstu)

EN

The main aim of this paper is to review and evaluate the selected scientific theories about the BI systems, especially relating to the analysis of user needs and models of Maturity Models of BI. For realization of this objective different methods were used, primarily bibliographic analysis method, descriptive and inferential methods and the method of synthesis. The paper is addressed to the persons who are interested in developing the theory and methodology for the BI systems, as well as business representatives interested in the use of BI in the organizations. (original abstract)

Słowa kluczowe

PL

Systemy Business Intelligence; Systemy wspomagania decyzji

EN

Business Intelligence systems; Decision Support Systems (DSS)

• Czasopismo: Studia Ekonomiczne / Uniwersytet Ekonomiczny w Katowicach
• Rocznik: 2012
• Numer: nr 113 Systemy inteligencji biznesowej jako przedmiot badań ekonomicznych
• Strony: 11--26

Twórcy

autor

Celina M. Olszak

• Uniwersytet Ekonomiczny w Katowicach

Bibliografia

• Adelman S., Moss L.: Data Warehouse Project Management. Sadle River, Addison- -Wesley, New York 2000.
• Alter A.: A Work System View of DSS in its Forth Decade. "Decision Support Systems" 2004, No. 38 (3).
• Anandarajan M.A. and Srinivasan C.A.: Business Intelligence Techniques - A Perspective from Accounting and Finance. Springer, Berlin 2004.
• Baaras H. and Kemper H.G.: Management Support with Structured and Unstructured Data - An Integrated Business Intelligence Framework. "Information systems Management" 2008, No. 25(2).
• Business Objects: About Business Intelligence, http://www.businessobjects.com/ businessintelligence/default.asp?intcmp=ip_company2, 2007.
• Bruin T., Rosemann M., Freeze R., Kulkarni U.: Understanding the Main Phases of Developing a Maturity Assessment Model. In: Proceedings of ACIS. Sydney 2005.
• Clarabridge I.: Converging Text and VI: the Case for a Content Mining Platform. http://www.clarabridge.com/resources/downloads.php, wrzesień 2011.
• Cognos: Cognos 8 Business Intelligence: What Is Business Intelligence? Cognos Corporation. http://www.cognos.com/products/cognos8businessintelligence/businessvalue/ whatis-business-intelligence.html, July, 2007.
• Chung W., Chen H., Nunamaker J.F.: A Visual Framework for Knowledge Discovery on the Web: An Empirical Study of Business Intelligence Exploration. "Journal of Management Information Systems" 2005, No. 21 (4).
• Davenport T.H., Harris J.G., Morison R.: Analytics at Work: Smarter Decisions, Better Results. Harvard Business Press, Boston 2010.
• Deng R.: Business Intelligence Maturity Hierarchy: A New Perspective from Knowledge Management, Information Management. http://www.information management.com/infodirect/20070323/1079089-1.html, wrzesień 2011.
• Eckerson W.W.: Gauge Your Data Warehousing Maturity. "DM Review" 2004, Vol. 14, No. 11.
• Eckerson W.: Smart Companies in the 21st Century: The Secrets of Creating Successful Business Intelligence Solutions. TDWI The Data Warehousing Institute Report Series, 2003. Retrieved from http://www.tdwi.org.
• Fletcher H.G., Surya B.Y.: Business Intelligence Conceptual Model. "International Journal of Business Intelligence Research" 2011, No. 292.
• Fraser P., Moultrie J., Gregory M.: The Use of Maturity Models/Grids as a Tool in Assessing Product Development Capability. In: Proceedings of IEM. Cambrige 2002.
• Gangadharan G., Swami S.: Business Intelligence Systems: Design and Implementation Strategies. In: 26th International Conference of Information Technology Interfaces (ITI), 2004.
• Gibson C.F., Nolan R.L.: Managing the Four Stages Of EPD Growth. "Harvard Business Review" 1974, Vol. 52, No. 1.
• Glancy F.H., Yadav S.B.: Business Intelligence Conceptual Model. "International Journal of Business Intelligence Research" 2011, No. 2(2).
• Green A.: Building Blocks to a Knowledge Valuation System (KVS). "The Journal of Information and Knowledge Management Systems", No. 36(2).
• Hagerty J.: AMR Research's Business Intelligence/ Performance Management Maturity Model. Version2:http://www.eurim.org.uk/activities/ig/voi/AMR_Researchs_Business_Intelligence.pdf,wrzesień 2011.
• Hannula M., Pirttimaki V.: Business Intelligence Empirical Study on the top 50 Finnish companies. "Journal of American Academy of Business" 2003, No. 2 (2).
• Hostmann B.: Business Intelligence Scenario. Gartner Business Intelligence Summit. Gartner Research, London 2007.
• Ing S.: A Strategic Approach to Intelligence. SAScom Magazine. http://www.sas.com/news/sascom/2007q3/column_nextpractices.html, 2007.
• Inmon W.H., Strauss D. and Neushloss G.: DW 2.0: The Architecture for the Next Generation of Data Warehousing. Elsevier Science, Amsterdam 2008.
• Jourdan Z., Rainer R.K., Marshall T.E.: Business Intelligence: An Analysis of the Literature."Information Systems Management" 2008, No. 25 (2).
• Kulkarni J., King R.: Business Intelligence Systems and Data Mining. SAS Institute 1997.
• Lahramnn G., Marx F., Winter R., Wortmann F.: Business Intelligence Maturity: Development and Evaluation of a Theoretical Model. In: Proceedings of the 44 Hawaii International Conference on System Science, 2011.
• Lahramnn G., Marx F., Winter R., Wortmann F.: Business Intelligence Maturity Models: An Overview. In: itAIS. Springer, Naples 2010.
• Lonnqvist A., Pirttimaki V.: The Measurement of Business Intelligence. "Business Intelligence" 2006, No. 23 (1).
• Luhn H.P.: A Business Intelligence Systems. "IBM Journal of Research and Development" 1958, No. 2(4).
• Markarian J., Brobst S., & Bedell J.: Critical Success Factors Deploying Pervasive BI.USA: Informatica, Teradata, MicroStrategy, http://www.teradata.com/t/WorkArea/DownloadAsset.aspx?id=4605, 2007.
• Mettler T., Rosner P.: Situational Maturity Models as Instruments Artifacts for Organizational Design. In: Proceedings of DESRIST, New York 2009.
• Miller L., Schiller D., Rhone M.: Data Warehouse Maturity Assessment Service. TERADATA. http://www.teradata.com/assets/0/206/276/3457d45f-7327-4a36- b1dc-2e5daae3d269.pdf, wrzesień 2011.
• Moss L., Atre S.: Business Intelligence Roadmap: The Complete Lifecycle for Decision-Support Applications. Addison-Wesley, Boston, MA 2003.
• Moss L., Hoberman S.: The Importance of Data Modeling as a Foundation for Business Insight. Teradata 2004.
• Negash S., Gray P.: Business Intelligence. In: Decision Support Systems. Ed. F. Burstein and C.W. Holsapple. Springer, Berlin, Heidenberg 2008.
• Negash S.: Business Intelligence. "Communications of Association for Information Systems" 2004, No. 13.
• Negash S., Gray P.: Business intelligence. Ninth Americas Conference on Information Systems, 2003.
• O'Brien J.A. and Marakas G.M.: Introduction to Information Systems (13th ed.). McGrawHill, New York 2007.
• Olszak C.M.: Tworzenie i wykorzystywanie systemów Business Intelligence na potrzeby współczesnej organizacji. AE, Katowice 2007.
• Olszak C.M., . Ziemba E: Business Intelligence as a key to Management of an Enterprise. In: Informing Science and IT Education. Ed. by Cohen, E. & Boyd E. Santa Rosa: The Informing Science Institute 2003. Available at: http://proceedings. informingscience.org/IS2003Proceedings/docs/109Olsza.pdf
• Oracle: Oracle Business Intelligence and Enterprise Performance Management. http://www.oracle.com/solutions/business_intelligence/indx.html
• SAS, Information Evaluation Model. http://www.sas.com/software/iem/, wrzesień 2011.
• Rajteric I.H.: Overview of Business Intelligence Maturity Models. "Management" 2010, Vol. 15.
• Strange K.F. : Making BI and Data Warehousing Strategic: The Key Issues. LE-1904691. Gartner Group 2009.
• The HP Business Intelligence Maturity Model. Describing the BI Journal. Hewlett- -Packard. http://www.techrepublic.com/whitepapers/the-hp-business-intelligence -maturity-model-describing-the-bi-journey/1129995, wrzesień 2011.
• Turban E., Sharda R., Aronson J., King D.: Business Intelligence. Prentice Hall, New Jersey 2007.
• Watson H.J., Ariyachandra T., Matyska R.J.: Data Warehousing Stags of Growth. "Information Systems Management" 2011, Vol. 18, No. 3; SAS, Information Evaluation Model: http://www.sas.com/software/iem/, wrzesień 2011.
• Watson H.J., Fuller C., Ariyachandra T.: Data warehouse governance: Best practices at Blue Cross and Blue Shield of North Carolina. Decision Support Systems, No. 38 (3), 2004.
• Williams S., Williams N.: The Profit Impact of Business Intelligence. Morgan Kaufmann, San Francisco 2007.
• White C.: Now is the Right Time for Real-time BI. "Information Management Magazine". Retrieved from http://www.dmreview.com, 2004, September,
• Whitehorn M., Whitehorn M.: Business Intelligence: The IBM Solution Datawarehousing and OLAP. Springer-Verlag, IBM, New York 1999.
• Wixom B.H., Watson H.J.: The BI-Based Organization. "International Journal of Business Intelligence Research" 2010, No. 1.