Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/46380

TítuloThe data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age
Autor(es)Costa, Carlos
Santos, Maribel Yasmina
Palavras-chaveConceptual model
Data science
Data scientist
Knowledge
Skills
Data2017
EditoraElsevier 1
RevistaInternational Journal of Information Management
CitaçãoCosta, Carlos and Maribel Yasmina Santos, “The data scientist profile and its representativeness in the European e-Competence framework and the skills framework for the information age”, International Journal of Information Management, http://dx.doi.org/10.1016/j.ijinfomgt.2017.07.010
Resumo(s)The activities in our current world are mainly supported by data-driven web applications, making extensive use of databases and data services. Such phenomenon led to the rise of Data Scientists as professionals of major relevance, which extract value from data and create state-of-the-art data artifacts that generate even more in- creased value. During the last years, the term Data Scientist attracted significant attention. Consequently, it is relevant to understand its origin, knowledge base and skills set, in order to adequately describe its profile and distinguish it from others like Business Analyst. This work proposes a conceptual model for the professional profile of a Data Scientist and evaluates the representativeness of this profile in two commonly recognized competences/skills frameworks in the field of Information and Communications Technology (ICT), namely in the European e-Competence (e-CF) framework and the Skills Framework for the Information Age (SFIA). The results indicate that a significant part of the knowledge base and skills set of Data Scientists are related with ICT competences/skills, including programming, machine learning and databases. The Data Scientist professional profile has an adequate representativeness in these two frameworks, but it is mainly seen as a multi-disciplinary profile, combining contributes from different areas, such as computer science, statistics and mathematics.
TipoArtigo
URIhttps://hdl.handle.net/1822/46380
DOI10.1016/j.ijinfomgt.2017.07.010
ISSN0268-4012
e-ISSN0143-6236
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals

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Este trabalho está licenciado sob uma Licença Creative Commons Creative Commons

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