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Big Data Framework for Agile Business (BDFAB) As a Basis for Developing Holistic Strategies in Big Data Adoption

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Big Data and Visual Analytics

Abstract

The Big Data Framework for Agile Business (BDFAB) is the result of exploration of the value of Big data technologies and analytics to business. BDFAB is based on literature review, modeling, experimentation and practical application. BDFAB incorporates multiple disciplines of Information Technology, Business Innovation, Sociology and Psychology (people and behavior, Social-Mobile media), Finance (ROI), Processes (Agile), User Experience, Analytics (descriptive, predictive and prescriptive) and Staff Up-skilling (HR). This paper presents the key elements of the framework comprising agile values, roles, building blocks, artifacts, conditions, agile practices and a compendium (repository). The building blocks themselves are made up of five modules: business decisions, Data—technology and analytics, user experience-operational excellence, quality dimensions and people—capabilities. As such, BDFAB exhibits an interdisciplinary approach to Big Data adoption in practice.

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References

  1. Unhelkar, B.: The Art of Agile Practice: A Composite Approach for Projects and Organizations. CRC/Auerbach, New York/Boca Raton (2013)

    Google Scholar 

  2. Mistry, N., Unhelkar, B.: Composite agile method and strategy: a balancing act. Presented at the Agile Testing Leadership Conference 2015 – held 21st Aug, 2015 in Sydney, Australia; (Organized by Unicom) (2015)

    Google Scholar 

  3. Agile Manifesto for Agile Software Development: viewed 9 March 2009, http://www.agilemanifesto.org/ (2001)

  4. Fowler, M., Highsmith, J.: The agile manifesto, Tech Web, viewed 9 March 2009, http://www.ddj.com/architect/184414755 (2001)

  5. Coffin, R., Lane, D.: A practical guide to seven agile methodologies, part 1, Jupitermedia Corporation, viewed 29 September 2009, http://www.devx.com/architect/Article/32761/1954 (2007)

  6. Boehm, B.: Get ready for agile methods, with care. IEEE Computer. 35(1), 64–69 (2002)

    Google Scholar 

  7. Unhelkar, B.: Lean-agile tautology. Cutter, Arlington (2014)

    Google Scholar 

  8. Lanier, J.: The frontier between us. Commun. ACM. 40(2), 55–56 (1997)

    Article  Google Scholar 

  9. DeMarco, T., Lister, T.: Peopleware: Productive Projects and Team. Dorset House, New York (1987)

    Google Scholar 

  10. Weinberg, G.M.: The Psychology of Computer Programming. Van Nostrand Reinhold, New York (1971)

    Google Scholar 

  11. Constantine, L.: Panel on “soft issues and other hard problems in software development.” In: OOPSLA’96, San Jose, California, USA, October 1996 (1996)

    Google Scholar 

  12. Constantine, L.: Constantine on Peopleware. Yourdon, Raleigh, NC (1995)

    Google Scholar 

  13. Unhelkar, B.: Games IT people play, information age, publication of the Australian Computer Society, June/July, 2003, pp. 25–29 (2003)

    Google Scholar 

  14. Levison, M.: “Why agile fails at scale: the human side” Agile Product & Project Management, Cutter E-Mail Advisors, USA 15th Dec, 2011 (2011)

    Google Scholar 

  15. Evernden, R.: Information architecture: dealing with too much data, Cutter executive report, Boston, USA (2012)

    Google Scholar 

  16. Unhelkar, B.: Agile in practice: a composite approach. Cutter Consortium Agile Product & Project Management Executive Report, vol. 11, no. 1, Boston, USA (2010)

    Google Scholar 

  17. Lampitt, A.: Relentless data growth : the big data journey has begun. In: InfoWorld (2012). https://www.infoworld.com/article/2607256/big-data/the-big-data-journey-has-begun.html. Accessed 7 Oct 2017

  18. Kellen, V.: Cutter E-mail advisory. https://www.cutter.com/article/big-data-big-denial-377591 (2013). Accessed 18 April 2013

  19. Shah, S., Horne, A., Capellá, J.: Good data won’t guarantee good decisions. Harv. Bus. Rev. 90(4), (2012). https://hbr.org/2012/04/good-data-wont-guarantee-good-decisions

  20. LaValle, S., Lesser, E., Shockley, R., Hopkins, M.S., Kruschwitz, N.: Big data, analytics and the path from insights to value. MIT Sloan Manag. Rev. 52(2, Winter), 21 (2011)

    Google Scholar 

  21. Sathi, A.: Big data analytics: disruptive technologies for changing the game, MC Press Online, LLC, Boise ID 83703, USA. © IBM Corporation (2012)

    Google Scholar 

  22. Davenport, T.H.: Competing on analytics. Harv. Bus. Rev. 99–107 (2006). https://hbr.org/2006/01/competing-on-analytics

  23. Kudyba, S.: Big Data, Mining, and Analytics: Components of Strategic Decision Making. CRC/Auerbach, New York/Boca Raton (2014)

    Book  Google Scholar 

  24. Moss, L.T., Adelman, S.: The role of chief data officer in the 21st century. Cutter exec report, vol. 13. Cutter Consortium, Boston (2013)

    Google Scholar 

  25. McKinsey report on Big Data.: http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation viewed on 30th April, 2017 (2011)

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Acknowledgment

University of South Florida, Sarasota-Manatee campus; MethodScience.

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Authors and Affiliations

  1. University of South Florida, Sarasota-Manatee Campus, Sarasota, FL, USA

    Bhuvan Unhelkar

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  1. Bhuvan Unhelkar
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Correspondence to Bhuvan Unhelkar .

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Editors and Affiliations

  1. Department of Computer Science, Texas A&M University-Commerce, Commerce, Texas, USA

    Sang C. Suh

  2. Department of Electrical and Computer Engineering, The University of Alabama at Birmingham, Birmingham, Alabama, USA

    Thomas Anthony

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Unhelkar, B. (2017). Big Data Framework for Agile Business (BDFAB) As a Basis for Developing Holistic Strategies in Big Data Adoption. In: Suh, S., Anthony, T. (eds) Big Data and Visual Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-63917-8_5

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  • DOI: https://doi.org/10.1007/978-3-319-63917-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63915-4

  • Online ISBN: 978-3-319-63917-8

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