Comparing Data Science Project Management Methodologies via a Controlled Experiment

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dc.contributor.authorSaltz, Jeffrey
dc.contributor.authorshamshurin, Ivan
dc.contributor.authorCrowston, Kevin
dc.date.accessioned2016-12-29T00:27:38Z
dc.date.available2016-12-29T00:27:38Z
dc.date.issued2017-01-04
dc.description.abstractData 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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.120
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41273
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBig Data
dc.subjectData Science
dc.subjectMethodology
dc.subjectProject Management
dc.titleComparing Data Science Project Management Methodologies via a Controlled Experiment
dc.typeConference Paper
dc.type.dcmiText

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