Process mining techniques applied in industry

Detalhes bibliográficos
Autor(a) principal: Pigozzi, Lorenzo
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/145482
Resumo: Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
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spelling Process mining techniques applied in industryProcess MiningProcess ScienceData ScienceBPMProcess AnalysisNokiaCelonisInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsGiven the overview of today’s information era, several scientific fields related to data raised. Process Mining is relatively new and it aims to leverage merged techniques from two separate scientific areas: Business Process Management and Data Science. The main purpose of Process Mining is the discovery, monitoring and improvement of real processes. As a result, in the last few years, Process Mining has increased remarkably, and the importance of the process insights has become more and more relevant, directly proportional to the amount and quality of data that supports the analyses. As a Data Engineer Intern at Nokia, I had the opportunity to be involved in the development phase of two business cases, being part of a team that has the main objective of exploring and analyzing several business processes within the company leveraging Data Science techniques.Jesus, Frederico Miguel Campos Cruz Ribeiro deRUNPigozzi, Lorenzo2022-11-14T17:17:52Z2022-10-252022-10-25T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/145482TID:203097483enginfo: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:RCAAP2024-03-11T05:25:53Zoai:run.unl.pt:10362/145482Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:52:06.162115Repositório 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 Process mining techniques applied in industry
title Process mining techniques applied in industry
spellingShingle Process mining techniques applied in industry
Pigozzi, Lorenzo
Process Mining
Process Science
Data Science
BPM
Process Analysis
Nokia
Celonis
title_short Process mining techniques applied in industry
title_full Process mining techniques applied in industry
title_fullStr Process mining techniques applied in industry
title_full_unstemmed Process mining techniques applied in industry
title_sort Process mining techniques applied in industry
author Pigozzi, Lorenzo
author_facet Pigozzi, Lorenzo
author_role author
dc.contributor.none.fl_str_mv Jesus, Frederico Miguel Campos Cruz Ribeiro de
RUN
dc.contributor.author.fl_str_mv Pigozzi, Lorenzo
dc.subject.por.fl_str_mv Process Mining
Process Science
Data Science
BPM
Process Analysis
Nokia
Celonis
topic Process Mining
Process Science
Data Science
BPM
Process Analysis
Nokia
Celonis
description Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
publishDate 2022
dc.date.none.fl_str_mv 2022-11-14T17:17:52Z
2022-10-25
2022-10-25T00:00:00Z
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/10362/145482
TID:203097483
url http://hdl.handle.net/10362/145482
identifier_str_mv TID:203097483
dc.language.iso.fl_str_mv eng
language eng
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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)
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