Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41273

Comparing Data Science Project Management Methodologies via a Controlled Experiment

File Size Format  
paper0124.pdf 1.06 MB Adobe PDF View/Open

Item Summary

Title:Comparing Data Science Project Management Methodologies via a Controlled Experiment
Authors:Saltz, Jeffrey
shamshurin, Ivan
Crowston, Kevin
Keywords:Big Data
Data Science
Methodology
Project Management
Date Issued:04 Jan 2017
Abstract:Data Science is an emerging field with a significant research focus on improving the techniques available to analyze data. However, there has been much less focus on how people should work together on a data science project. In this paper, we report on the results of an experiment comparing four different methodologies to manage and coordinate a data science project. We first introduce a model to compare different project management methodologies and then report on the results of our experiment. The results from our experiment demonstrate that there are significant differences based on the methodology used, with an Agile Kanban methodology being the most effective and surprisingly, an Agile Scrum methodology being the least effective.
Pages/Duration:10 pages
URI/DOI:http://hdl.handle.net/10125/41273
ISBN:978-0-9981331-0-2
DOI:10.24251/HICSS.2017.120
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Big Data and Analytics: Concepts, Methods, Techniques and Applications Minitrack


Please email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.

This item is licensed under a Creative Commons License Creative Commons