Forecasting sales and transactions of fast-food stores: a proof of concept

Detalhes bibliográficos
Autor(a) principal: Mousinho, Cristina Isabel Palma
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/10362/135048
Resumo: Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
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spelling Forecasting sales and transactions of fast-food stores: a proof of conceptMachine LearningForecasting demandTime seriesARIMAFacebook ProphetInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceAs time goes on, more and more clients look for solutions to their data-related problems. During a 9-month internship at the Portuguese consulting company Noesis, a request was presented by a customer that wished to improve the forecasting capabilities of their fast-food chain, on sales and transactions, for four different distribution channels, and globally. Following a data analytics approach, hundreds of time series were examined, external variables were added, and two algorithms were used - ARIMA and Facebook’s Prophet. Both models were evaluated, and as each of them performed better in different segments, a hybrid system was implemented, successfully completing the task at hand. Based on the results, future improvements and recommendations were also identified.Castelli, MauroLopes, Pedro FreitasRUNMousinho, Cristina Isabel Palma2022-03-23T14:23:24Z2022-01-282022-01-28T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/135048TID:202970973enginfo: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:RCAAP2024-03-11T05:13:30Zoai:run.unl.pt:10362/135048Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:48:17.830191Repositório 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 Forecasting sales and transactions of fast-food stores: a proof of concept
title Forecasting sales and transactions of fast-food stores: a proof of concept
spellingShingle Forecasting sales and transactions of fast-food stores: a proof of concept
Mousinho, Cristina Isabel Palma
Machine Learning
Forecasting demand
Time series
ARIMA
Facebook Prophet
title_short Forecasting sales and transactions of fast-food stores: a proof of concept
title_full Forecasting sales and transactions of fast-food stores: a proof of concept
title_fullStr Forecasting sales and transactions of fast-food stores: a proof of concept
title_full_unstemmed Forecasting sales and transactions of fast-food stores: a proof of concept
title_sort Forecasting sales and transactions of fast-food stores: a proof of concept
author Mousinho, Cristina Isabel Palma
author_facet Mousinho, Cristina Isabel Palma
author_role author
dc.contributor.none.fl_str_mv Castelli, Mauro
Lopes, Pedro Freitas
RUN
dc.contributor.author.fl_str_mv Mousinho, Cristina Isabel Palma
dc.subject.por.fl_str_mv Machine Learning
Forecasting demand
Time series
ARIMA
Facebook Prophet
topic Machine Learning
Forecasting demand
Time series
ARIMA
Facebook Prophet
description Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
publishDate 2022
dc.date.none.fl_str_mv 2022-03-23T14:23:24Z
2022-01-28
2022-01-28T00:00:00Z
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/10362/135048
TID:202970973
url http://hdl.handle.net/10362/135048
identifier_str_mv TID:202970973
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)
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
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repository.mail.fl_str_mv
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