Risk management in data science projects in Portugal
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/23892 |
Resumo: | The increasing popularity of data projects has influenced many development initiatives aimed at improving business performance and decision-making. However, Data Science projects carry in their essence a set of specific risks and uncertainties. Good risk management is one of the most crucial components of a project. Its effective conduct increases the probability of project success, however, it is necessary to understand the environment and the components surrounding risks. In this context, this investigation was conducted to create a base list of the risks of Data Science projects and their surrounding factors. This research was guided by the Design Science Research approach and the data collection process was conducted through the Delphi technique, where it was possible to identify and analyze the risks, their factors, the failure scenarios of the projects, and to understand the contribution of the development methodologies in these projects. The study enabled the creation of an artifact, consisting of a list of specific data management-related risks and best practice recommendations. However, it was found that more than half of the risks at the top of the rankings are similar to the risks of other types of IT projects. This research contributes a consolidated list of 25 risks of Data Science projects intending to help decrease the failures of projects in this area. |
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Risk management in data science projects in PortugalData scienceRisk managementDelphi techniqueData science riskProject successDesign Science Research (DSR)Ciência de dadosGestão do riscoTécnica de DelphiRiscos de ciência de dadosSucesso do projectoThe increasing popularity of data projects has influenced many development initiatives aimed at improving business performance and decision-making. However, Data Science projects carry in their essence a set of specific risks and uncertainties. Good risk management is one of the most crucial components of a project. Its effective conduct increases the probability of project success, however, it is necessary to understand the environment and the components surrounding risks. In this context, this investigation was conducted to create a base list of the risks of Data Science projects and their surrounding factors. This research was guided by the Design Science Research approach and the data collection process was conducted through the Delphi technique, where it was possible to identify and analyze the risks, their factors, the failure scenarios of the projects, and to understand the contribution of the development methodologies in these projects. The study enabled the creation of an artifact, consisting of a list of specific data management-related risks and best practice recommendations. However, it was found that more than half of the risks at the top of the rankings are similar to the risks of other types of IT projects. This research contributes a consolidated list of 25 risks of Data Science projects intending to help decrease the failures of projects in this area.A grande popularidade dos projetos de dados tem influenciado muitas iniciativas de desenvolvimento com o intuito de melhorar a performance dos negócios e tomadas de decisões. Contudo, os projetos de Ciência de Dados carregam na sua essência um conjunto de riscos e incertezas específicos. Ter uma boa gestão de risco é um dos componentes mais cruciais de um projeto. A sua eficaz conduta aumenta as probabilidades de sucesso do projeto, contudo, é necessário compreender os componentes envolventes aos riscos. Neste contexto, foi conduzida esta investigação com o propósito de criar uma lista base dos riscos dos projetos de Ciência de Dados e seus fatores envolventes. Esta investigação foi guiada pela abordagem de Design Science Research e o processo de recolha de dados foi conduzida através da técnica de Delphi, onde foi possível identificar e analisar os riscos, seus fatores, os cenários de falhas dos projetos e perceber o contributo das metodologias de desenvolvimento nesses projetos. O estudo permitiu a criação de um artefacto, que consiste em uma lista de riscos específicos relacionados com a gestão de dados e recomendações de boas práticas. Contudo, foi possível verificar que mais de metade dos riscos no topo das classificações são semelhantes aos riscos de outros tipos de projetos de IT. Esta investigação contribui com uma lista consolidada de 25 riscos dos projetos de Ciência de Dados com o intuído de auxiliar na diminuição das falhas dos projetos deste âmbito.2022-12-10T00:00:00Z2021-12-10T00:00:00Z2021-12-102021-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/23892TID:202830470engVarela, Ana Cristina Afonsoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:24:25Zoai:repositorio.iscte-iul.pt:10071/23892Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:11:06.909825Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Risk management in data science projects in Portugal |
title |
Risk management in data science projects in Portugal |
spellingShingle |
Risk management in data science projects in Portugal Varela, Ana Cristina Afonso Data science Risk management Delphi technique Data science risk Project success Design Science Research (DSR) Ciência de dados Gestão do risco Técnica de Delphi Riscos de ciência de dados Sucesso do projecto |
title_short |
Risk management in data science projects in Portugal |
title_full |
Risk management in data science projects in Portugal |
title_fullStr |
Risk management in data science projects in Portugal |
title_full_unstemmed |
Risk management in data science projects in Portugal |
title_sort |
Risk management in data science projects in Portugal |
author |
Varela, Ana Cristina Afonso |
author_facet |
Varela, Ana Cristina Afonso |
author_role |
author |
dc.contributor.author.fl_str_mv |
Varela, Ana Cristina Afonso |
dc.subject.por.fl_str_mv |
Data science Risk management Delphi technique Data science risk Project success Design Science Research (DSR) Ciência de dados Gestão do risco Técnica de Delphi Riscos de ciência de dados Sucesso do projecto |
topic |
Data science Risk management Delphi technique Data science risk Project success Design Science Research (DSR) Ciência de dados Gestão do risco Técnica de Delphi Riscos de ciência de dados Sucesso do projecto |
description |
The increasing popularity of data projects has influenced many development initiatives aimed at improving business performance and decision-making. However, Data Science projects carry in their essence a set of specific risks and uncertainties. Good risk management is one of the most crucial components of a project. Its effective conduct increases the probability of project success, however, it is necessary to understand the environment and the components surrounding risks. In this context, this investigation was conducted to create a base list of the risks of Data Science projects and their surrounding factors. This research was guided by the Design Science Research approach and the data collection process was conducted through the Delphi technique, where it was possible to identify and analyze the risks, their factors, the failure scenarios of the projects, and to understand the contribution of the development methodologies in these projects. The study enabled the creation of an artifact, consisting of a list of specific data management-related risks and best practice recommendations. However, it was found that more than half of the risks at the top of the rankings are similar to the risks of other types of IT projects. This research contributes a consolidated list of 25 risks of Data Science projects intending to help decrease the failures of projects in this area. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-10T00:00:00Z 2021-12-10 2021-11 2022-12-10T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/23892 TID:202830470 |
url |
http://hdl.handle.net/10071/23892 |
identifier_str_mv |
TID:202830470 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799134665429221376 |