Designing a collaborative AutoML tool to help organizations become data-driven

Detalhes bibliográficos
Autor(a) principal: Mattmüller, Jens Marius
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/148721
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
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spelling Designing a collaborative AutoML tool to help organizations become data-drivenAutoMLcollaborationData-driven decision makingMachine LearningDesign Science ResearchDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da InformaçãoDomínio/Área Científica::Ciências Sociais::Economia e GestãoDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThis study aims to address a lack of knowledge in the emerging field of automated machine learning (AutoML) techniques. While the AutoML technology develops further and further and provides increasingly robust and interesting results, there is only little to no current research on how this technology can be adopted and scaled across different functions and teams of any organization. Thus, this study raises the research question of how an information system that leverages AutoML techniques can empower organizations and their non-technical individuals to collaborate on and adopt machine learning techniques in their daily lives to unlock the value of available data. To gain a clear analytical lens, this study is conducted in the environment of Management Consulting Companies (MCCs) as they span all industries and multiple tasks within diverse organizations and therefore promise a good transfer of knowledge to other application areas. A special emphasis is given to non-technical users and the possibilities of them participating in such a system as that has the potential to reach a large number of real-world practitioners. The identified problem is tackled with a Design Science Research (DSR) approach. A workflow of how an information system can support its users to leverage AutoML serves as an artifact that is evaluated by experts. Learnings from the theory behind the proposal and its evaluation contribute to literature around AutoML and the transformation of the MCC industry as well as practical applications in both fields. Results suggest that AutoML is best used to conduct quick experiments and find out which applications have the highest business value before involving experts. Major challenges are to help non-technical users define a use case and prepare data.Santos, Vitor Manuel Pereira Duarte dosRUNMattmüller, Jens Marius2023-02-06T13:26:47Z2023-01-242023-01-24T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/148721TID:203223020enginfo: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:RCAAP2024-03-11T05:30:23Zoai:run.unl.pt:10362/148721Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:53:28.014917Repositório 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 Designing a collaborative AutoML tool to help organizations become data-driven
title Designing a collaborative AutoML tool to help organizations become data-driven
spellingShingle Designing a collaborative AutoML tool to help organizations become data-driven
Mattmüller, Jens Marius
AutoML
collaboration
Data-driven decision making
Machine Learning
Design Science Research
Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Designing a collaborative AutoML tool to help organizations become data-driven
title_full Designing a collaborative AutoML tool to help organizations become data-driven
title_fullStr Designing a collaborative AutoML tool to help organizations become data-driven
title_full_unstemmed Designing a collaborative AutoML tool to help organizations become data-driven
title_sort Designing a collaborative AutoML tool to help organizations become data-driven
author Mattmüller, Jens Marius
author_facet Mattmüller, Jens Marius
author_role author
dc.contributor.none.fl_str_mv Santos, Vitor Manuel Pereira Duarte dos
RUN
dc.contributor.author.fl_str_mv Mattmüller, Jens Marius
dc.subject.por.fl_str_mv AutoML
collaboration
Data-driven decision making
Machine Learning
Design Science Research
Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic AutoML
collaboration
Data-driven decision making
Machine Learning
Design Science Research
Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
publishDate 2023
dc.date.none.fl_str_mv 2023-02-06T13:26:47Z
2023-01-24
2023-01-24T00:00:00Z
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/10362/148721
TID:203223020
url http://hdl.handle.net/10362/148721
identifier_str_mv TID:203223020
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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