Data Science Canvas: Evaluation of a Tool to Manage Data Science Projects

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dc.contributor.authorNeifer, Thomas
dc.contributor.authorLawo, Dennis
dc.contributor.authorEsau, Margarita
dc.date.accessioned2020-12-24T20:07:45Z
dc.date.available2020-12-24T20:07:45Z
dc.date.issued2021-01-05
dc.description.abstractData emerged as a central success factor for companies to benefit from digitization. However, the skills in successfully creating value from data – especially at the management level – are not always profound. To address this problem, several canvas models have already been designed. Canvas models are usually created to write down an idea in a structured way to promote transparency and traceability. However, some existing data science canvas models mainly address developers and are thus unsuitable for decision-makers and communication within interdisciplinary teams. Based on a literature review, we identified influencing factors that are essential for the success of data science projects. With the information gained, the Data Science Canvas was developed in an expert workshop and finally evaluated by practitioners to find out whether such an instrument could support data-driven value creation.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.657
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/71277
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th 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.subjectAdvances in Design Science Research
dc.subjectdata literacy
dc.subjectdata science
dc.subjectdata science canvas
dc.titleData Science Canvas: Evaluation of a Tool to Manage Data Science Projects
prism.startingpage5399

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