Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems

Autores
Ferrer Daub, Facundo Javier
Año de publicación
2017
Idioma
inglés
Tipo de recurso
tesis de maestría
Estado
versión aceptada
Colaborador/a o director/a de tesis
Srur, Leandro
Descripción
Since 1991 with the birth of the World Wide Web the rate of data growth has been growing with a record level in the last couple of years. Big companies tackled down this data growth with expensive and enormous data centres to process and get value of this data. From social media, Internet of Things (IoT), new business process, monitoring and multimedia, the capacities of those data centres started to be a problem and required continuos and expensive expansion. Thus, Big Data was something that only a few were able to access. This changed fast when Amazon launched Amazon Web Services (AWS) around 15 years ago and gave the origins to the public cloud. At that time, the capabilities were still very new and reduced but 10 years later the cloud was a whole new business that changed for ever the Big Data business. This not only commoditised computer power but it was accompanied by a price model that let medium and small players the possibility to access it. In consequence, new problems arised regarding the nature of these distributed systems and the software architectures required for proper data processing. The present job analyse the type of typical Big Data workloads and propose an architecture for a cloud native data analysis pipeline. Lastly, it provides a chapter for tools and services that can be used in the architecture taking advantage of their open source nature and the cloud price models.
Fil: Ferrer Daub, Facundo Javier. Universidad Católica de Córdoba. Instituto de Ciencias de la Administración; Argentina
Fuente
Ferrer Daub, Facundo Javier (2017) Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems. Universidad Católica de Córdoba [Tesis de Maestría].
Materia
QA75 Equipos electrónicos. Informática
T Tecnología (General)
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
Repositorio
Producción Académica (UCC)
Institución
Universidad Católica de Córdoba
OAI Identificador
oai:pa.bibdigital.uccor.edu.ar:1524
Acceder
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oai_identifier_str oai:pa.bibdigital.uccor.edu.ar:1524
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network_name_str Producción Académica (UCC)
spelling Design and evaluation of a cloud native data analysis pipeline for cyber physical production systemsFerrer Daub, Facundo JavierQA75 Equipos electrónicos. InformáticaT Tecnología (General)Since 1991 with the birth of the World Wide Web the rate of data growth has been growing with a record level in the last couple of years. Big companies tackled down this data growth with expensive and enormous data centres to process and get value of this data. From social media, Internet of Things (IoT), new business process, monitoring and multimedia, the capacities of those data centres started to be a problem and required continuos and expensive expansion. Thus, Big Data was something that only a few were able to access. This changed fast when Amazon launched Amazon Web Services (AWS) around 15 years ago and gave the origins to the public cloud. At that time, the capabilities were still very new and reduced but 10 years later the cloud was a whole new business that changed for ever the Big Data business. This not only commoditised computer power but it was accompanied by a price model that let medium and small players the possibility to access it. In consequence, new problems arised regarding the nature of these distributed systems and the software architectures required for proper data processing. The present job analyse the type of typical Big Data workloads and propose an architecture for a cloud native data analysis pipeline. Lastly, it provides a chapter for tools and services that can be used in the architecture taking advantage of their open source nature and the cloud price models.Fil: Ferrer Daub, Facundo Javier. Universidad Católica de Córdoba. Instituto de Ciencias de la Administración; ArgentinaSrur, Leandro2017-03-01info:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_bdccinfo:ar-repo/semantics/tesisDeMaestriaapplication/pdfhttp://pa.bibdigital.ucc.edu.ar/1524/1/TM_FerrerDaub.pdf Ferrer Daub, Facundo Javier (2017) Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems. Universidad Católica de Córdoba [Tesis de Maestría]. reponame:Producción Académica (UCC)instname:Universidad Católica de Córdobaenghttp://pa.bibdigital.ucc.edu.ar/1524/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es2025-09-29T14:29:05Zoai:pa.bibdigital.uccor.edu.ar:1524instacron:UCCInstitucionalhttp://pa.bibdigital.uccor.edu.ar/Universidad privadaNo correspondehttp://pa.bibdigital.uccor.edu.ar/cgi/oai2bibdir@uccor.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:27182025-09-29 14:29:05.534Producción Académica (UCC) - Universidad Católica de Córdobafalse
dc.title.none.fl_str_mv Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
title Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
spellingShingle Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
Ferrer Daub, Facundo Javier
QA75 Equipos electrónicos. Informática
T Tecnología (General)
title_short Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
title_full Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
title_fullStr Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
title_full_unstemmed Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
title_sort Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems
dc.creator.none.fl_str_mv Ferrer Daub, Facundo Javier
author Ferrer Daub, Facundo Javier
author_facet Ferrer Daub, Facundo Javier
author_role author
dc.contributor.none.fl_str_mv Srur, Leandro
dc.subject.none.fl_str_mv QA75 Equipos electrónicos. Informática
T Tecnología (General)
topic QA75 Equipos electrónicos. Informática
T Tecnología (General)
dc.description.none.fl_txt_mv Since 1991 with the birth of the World Wide Web the rate of data growth has been growing with a record level in the last couple of years. Big companies tackled down this data growth with expensive and enormous data centres to process and get value of this data. From social media, Internet of Things (IoT), new business process, monitoring and multimedia, the capacities of those data centres started to be a problem and required continuos and expensive expansion. Thus, Big Data was something that only a few were able to access. This changed fast when Amazon launched Amazon Web Services (AWS) around 15 years ago and gave the origins to the public cloud. At that time, the capabilities were still very new and reduced but 10 years later the cloud was a whole new business that changed for ever the Big Data business. This not only commoditised computer power but it was accompanied by a price model that let medium and small players the possibility to access it. In consequence, new problems arised regarding the nature of these distributed systems and the software architectures required for proper data processing. The present job analyse the type of typical Big Data workloads and propose an architecture for a cloud native data analysis pipeline. Lastly, it provides a chapter for tools and services that can be used in the architecture taking advantage of their open source nature and the cloud price models.
Fil: Ferrer Daub, Facundo Javier. Universidad Católica de Córdoba. Instituto de Ciencias de la Administración; Argentina
description Since 1991 with the birth of the World Wide Web the rate of data growth has been growing with a record level in the last couple of years. Big companies tackled down this data growth with expensive and enormous data centres to process and get value of this data. From social media, Internet of Things (IoT), new business process, monitoring and multimedia, the capacities of those data centres started to be a problem and required continuos and expensive expansion. Thus, Big Data was something that only a few were able to access. This changed fast when Amazon launched Amazon Web Services (AWS) around 15 years ago and gave the origins to the public cloud. At that time, the capabilities were still very new and reduced but 10 years later the cloud was a whole new business that changed for ever the Big Data business. This not only commoditised computer power but it was accompanied by a price model that let medium and small players the possibility to access it. In consequence, new problems arised regarding the nature of these distributed systems and the software architectures required for proper data processing. The present job analyse the type of typical Big Data workloads and propose an architecture for a cloud native data analysis pipeline. Lastly, it provides a chapter for tools and services that can be used in the architecture taking advantage of their open source nature and the cloud price models.
publishDate 2017
dc.date.none.fl_str_mv 2017-03-01
dc.type.none.fl_str_mv info:eu-repo/semantics/masterThesis
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_bdcc
info:ar-repo/semantics/tesisDeMaestria
format masterThesis
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://pa.bibdigital.ucc.edu.ar/1524/1/TM_FerrerDaub.pdf
url http://pa.bibdigital.ucc.edu.ar/1524/1/TM_FerrerDaub.pdf
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://pa.bibdigital.ucc.edu.ar/1524/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Ferrer Daub, Facundo Javier (2017) Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems. Universidad Católica de Córdoba [Tesis de Maestría].
reponame:Producción Académica (UCC)
instname:Universidad Católica de Córdoba
reponame_str Producción Académica (UCC)
collection Producción Académica (UCC)
instname_str Universidad Católica de Córdoba
repository.name.fl_str_mv Producción Académica (UCC) - Universidad Católica de Córdoba
repository.mail.fl_str_mv bibdir@uccor.edu.ar
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score 12.559606

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