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2020 | z. 144 | 661--669
Tytuł artykułu

Supporting Reporting in Project Management

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Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: The article presents the results of qualitative research related to answering the question: "How can reporting be supported when there is no access to professional BI tools?". Design/methodology/approach: The answer to this question was set in the context of the BI layers proposed by Todd (todd 2017). This approach allowed one to determine, in each layer, operations performed on data that support reporting. The main research method was the participation observation made in the author's involvement in the project management team. Findings: Supporting reporting in project management when there is no access to professional BI tools needs strong technical competences and great creativity by the project management team in using applications such as spreadsheets or database tools. The most helpful functionalities provided by spreadsheets are text and search functions and the data conversion wizard. The most useful functionality provided by database tools was intelligent calculations made by queries and automatic report design provided by MS Access. Originality/value: The paper presents an examination of the set of operations and IT tools needed in a business analysis made in project management in a situation where there is no access to professional BI tools. (original abstract)
Rocznik
Numer
Strony
661--669
Opis fizyczny
Twórcy
autor
  • Silesian University of Technology
Bibliografia
  • 1. Abbott, D. (2014). Applied predictive analytics: Principles and techniques for the professional data analyst. John Wiley & Sons.
  • 2. Al-Sakran, H.O. (2014). Analysis of Business Analytics Curricula and Job Demand in Saudi Arabia. Life Science Journal (11:8), pp. 918-926.
  • 3. Bobriakov, I. (2018). Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018. Retrieved from https://www.kdnuggets.com/2018/02/comparative-analysis-top-6-bi- data-visualization-tools-2018.html.
  • 4. Chiang, R.H.L., Goes, P., and Stohr, E.A. (2012). Business Intelligence and Analytics Education, and Program Development: A Unique Opportunity for the Information Systems Discipline. ACM Transactions Management Information Systems. (3:3), pp. 12.
  • 5. Chung, L. (2019). Microsoft Access versus Microsoft Excel for Data Analysis and Reporting. Retrieved from http://www.fmsinc.com/MicrosoftAccess/DataAnalysis/versus- excel.html, 2019.06.20.
  • 6. Craig, W. (2019). How to Make Data Visualization Better with Gestalt Laws. Retrieved from https://www.webfx.com/blog/web-design/data-visualization-gestalt-laws/.
  • 7. Davis, G.A., Woratschek, C.R. (2015). Evaluating Business Intelligence/Business Analytics Software for Use in the Information Systems Curriculum. Information Systems Education Journal (13:1), pp. 23-29.
  • 8. Dykes, B. (2010). Reporting vs. Analysis: What's the Difference? Retrieved from https://theblog.adobe.com/reporting-vs-analysis-whats-the-difference/, 2010.10.19.
  • 9. Edgington, T.M. (2011). Introducing Text Analytics as a Graduate Business School Course. Journal of Information Technology Education: Innovations in Practice 10, pp. 207-234.
  • 10. Few, S.C. (2012). Show Me the Numbers. Analytics Press.
  • 11. Gorman, M.F., and Klimberg, R.K. (2014). Benchmarking Academic Programs in Business Analytics. Interfaces, (44:3), pp. 329-341.
  • 12. Green, A. (2010). Seven Free Data Wrangling Tools. Retrieved from https://www.varonis.com/blog/free-data-wrangling-tools/, 2010.10.30.
  • 13. Knaflic, C.N. (2015). Storytelling with data. New Jersey: Willey, Hoboken.
  • 14. Negash, S. (2004). Business intelligence. Communications of the Association for Information Systems, 13, 177-195.
  • 15. Pomykalski, J.J. (2014). Teaching Business Intelligence through Case Studies. Proceedings of the Information Systems Educators Conference, Baltimore, Maryland, USA.
  • 16. Presthus, W., and Bygstad, B. (2012). Business Intelligence in College: A Teaching Case with Real Life Puzzles. Journal of Information Technology Education: Innovations in Practice, 11, pp. 121-137.
  • 17. Sircar, S. (2009). Business Intelligence in the Business Curriculum. Communications of the Association for Information Systems, 24, pp. 289-302.
  • 18. Todd, J. (2017). Data-Driven Decisions: Business Intelligence (BI) Training Skills. All Theses And Dissertations, 127. Retrieved from http://dune.une.edu/theses/127.
  • 19. Wilder, C.R., & Ozgur, C.O. (2015). Business Analytics Curriculum for Undergraduate Majors. INFORMS Transactions on Education (15:2), pp. 180-187.
  • 20. Wixom, B., Ariyachandra, T., Douglas, D., Goul, M., Gupta, B., Lyer, L., Kulkarni, U., Mooney, J.G., Phillips-Wren, G., and Turetken, O. (2014). The Current State of Business Intelligence in Academia: The Arrival of Big Data. Communications of the Association for Information Systems, 34, pp. 1-13.
  • 21. Yau, N. (2013). Data points. Willey.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171597001

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