dc.contributor.author | GRABIS, Janis | |
dc.contributor.author | HAIDABRUS, Bohdan | |
dc.contributor.author | PROTSENKO, Serhiy | |
dc.contributor.author | PROTSENKO, Iryna | |
dc.contributor.author | ROVNA, Anna | |
dc.date.accessioned | 2019-10-31T12:18:55Z | |
dc.date.available | 2019-10-31T12:18:55Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | GRABIS, Janis, HAIDABRUS, Bohdan, PROTSENKO, Serhiy et al. Data Science approach for IT project management. In: Electronics, Communications and Computing: extended abstracts of the 10th Intern. Conf.: the 55th anniversary of Technical University of Moldova, Chişinău, October 23-26, 2019. Chişinău, 2019, p. 31. ISBN 978-9975-108-84-3. | en_US |
dc.identifier.isbn | 978-9975-108-84-3 | |
dc.identifier.uri | http://repository.utm.md/handle/5014/5774 | |
dc.description | Abstract | en_US |
dc.description.abstract | Majority of the IT companies realized that ability to analyse and use data, could be one of the key factors for increasing of number of successful projects, portfolios, programs. Key performance indicators based on data analysis helps organizations be more prosperous in a long term perspective. Also, statistical data are very useful for monitoring and evaluation of project results which are very important for managers, delivery directors, CTO and others high level management of company. The Data Science methods could make more efficient project management in several of business problems. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Tehnica UTM | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | machine learning | en_US |
dc.subject | project management | en_US |
dc.subject | data analysis | en_US |
dc.title | Data Science approach for IT project management | en_US |
dc.type | Article | en_US |
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