Abstract
Project management constitutes a powerful lever as organizations face increasing pressure to manage projects to budget, on time, and deliver more insights, in less time and with rapidly increasing amounts of data. This is critical especially in business analytics, with more than75% of organizations planning big data investments over the next several years. But the manipulation of massive amounts of data presents challenges – budgetary, time constraints, execution, proper manager skillsets, and such like. These challenges have cramped recent project rollouts, as only 37% of organizations have deployed big data projects in the past year; this suggests that filling the gap between data and insight remains a substantial hurdle as well as evolving need of project management for such projects. This chapter offers real-world examples of how project management professionals tackle big data challenges in a rapidly evolving, data-rich environment. Simultaneously, it establishes a bridge between business and academia as they both recognize the joint necessity to develop highly trained project managers to utilize the powerful and cutting edge analytical tools available to create value.
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References
Ahrens, S. (2014). What an IT project manager should know about analytics projects. SAS Voices. Retrieved from https://blogs.sas.com/content/sascom/2014/09/15/it-project-manager-and-analytics-projects/
Austin, R. D. (2013). Project management simulation: Scope, resources & time. Harvard Business Publishing Education. https://cb.hbsp.harvard.edu/cbmp/product/4700-HTM-ENG
Columbus, L. (2017). IBM predicts demand for data scientist will soar 28% by 2020. IBM White Paper. Retrieved from https://www.forbes.com/sites/louiscolumbus/2017/05/13/ibm-predicts-demand-for-data-scientists-will-soar-28-by-2020/#6519b2b97e3b
Gartner. (2013). Gartner predicts business intelligence and analytics will remain top focus for CIOs through 2017. Gartner News Article. Retrieved from http://www.gartner.com/newsroom/id/2637615
Hendershot, S. (2016). Data done right: Learning to target the right type of data can uncover insights that drive project success. PM Network, 30(3), 40–45.
Kisielnicki, J., & Misiak, A. M. (2016). Effectiveness of agile implementation methods in business intelligence projects from an end-user perspective. Informing Science: The International Journal of an Emerging Transdiscipline, 19, 161–172.
McMahon, A. (2016). All assumptions are false! 7 lessons I wish I paid more attention to on every predictive analytics project. Presidion White Paper. Retrieved from http://www.presidion.com/wp-content/uploads/2016/03/1603_AM_7Lessons_PA_Project.pdf
Project Management Institute. (2017). Project Management Body of Knowledge (PMBOK). 6th Edition. PMI Website. Retrieved from https://www.pmi.org/pmbok-guide-standards/foundational/pmbok/sixth-edition
Thomke, S. (2003). Experimentation matters: Unlocking the potential of new technologies for innovation (pp. 97–98). Boston: Harvard Business School Press.
Viaene, S., & Van den Bunder, A. (2011). The secrets to managing business analytics projects. MIT Sloan Management Review, 53(1), 65–69.
White, D. (2011). Agile BI – complementing traditional BI to address the shrinking decision-window. Aberdeen Group White Paper. Retrieved from https://www.montage.co.nz/assets/Brochures/Aberdeen-Agile-BI.pdf
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Shah, S., Gochtovtt, A., Baldini, G. (2019). Importance of Project Management in Business Analytics: Academia and Real World. In: Anandarajan, M., Harrison, T. (eds) Aligning Business Strategies and Analytics. Advances in Analytics and Data Science, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-93299-6_6
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DOI: https://doi.org/10.1007/978-3-319-93299-6_6
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