Extract, Transform, and Load data from Legacy Systems to Azure Cloud
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/10362/118629 |
Resumo: | Internship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business Intelligence |
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Extract, Transform, and Load data from Legacy Systems to Azure CloudModern data platformData lakeDelta lakeData integrationData transformationData loadingInternship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business IntelligenceIn a world with continuously evolving technologies and hardened competitive markets, organisations need to continually be on guard to grasp cutting edge technology and tools that will help them to surpass any competition that arises. Modern data platforms that incorporate cloud technologies, support organisations to strive and get ahead of their competitors by providing solutions that help them capture and optimally use untapped data, and scalable storages to adapt to ever-growing data quantities. Also, adopt data processing and visualisation tools that help to improve the decision-making process. With many cloud providers available in the market, from small players to major technology corporations, this offers much flexibility to organisations to choose the best cloud technology that will align with their use cases and overall products and services strategy. This internship came up at the time when one of Accenture’s significant client in the financial industry decided to migrate from legacy systems to a cloud-based data infrastructure that is Microsoft Azure cloud. During this internship, development of the data lake, which is a core part of the MDP, was done to understand better the type of challenges that can be faced when migrating data from on-premise legacy systems to a cloud-based infrastructure. Also, provided in this work, are the main recommendations and guidelines when it comes to performing a large scale data migration.Pinheiro, Flávio Luís PortasRUNJephte, Ioudom Foubi2021-06-01T10:02:12Z2021-05-202021-05-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/118629TID:202731391enginfo: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:RCAAP2024-03-11T05:01:25Zoai:run.unl.pt:10362/118629Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:43:55.633161Repositório 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 |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud |
title |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud |
spellingShingle |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud Jephte, Ioudom Foubi Modern data platform Data lake Delta lake Data integration Data transformation Data loading |
title_short |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud |
title_full |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud |
title_fullStr |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud |
title_full_unstemmed |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud |
title_sort |
Extract, Transform, and Load data from Legacy Systems to Azure Cloud |
author |
Jephte, Ioudom Foubi |
author_facet |
Jephte, Ioudom Foubi |
author_role |
author |
dc.contributor.none.fl_str_mv |
Pinheiro, Flávio Luís Portas RUN |
dc.contributor.author.fl_str_mv |
Jephte, Ioudom Foubi |
dc.subject.por.fl_str_mv |
Modern data platform Data lake Delta lake Data integration Data transformation Data loading |
topic |
Modern data platform Data lake Delta lake Data integration Data transformation Data loading |
description |
Internship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business Intelligence |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-01T10:02:12Z 2021-05-20 2021-05-20T00:00:00Z |
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/10362/118629 TID:202731391 |
url |
http://hdl.handle.net/10362/118629 |
identifier_str_mv |
TID:202731391 |
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 |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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 |
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1799138047902613504 |