An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/SAI.2017.8252125 http://hdl.handle.net/11449/179824 |
Resumo: | With the technologies proliferation for Internet, such as cloud computing, mobile devices, social media and the internet of things, small and medium enterprises, despite their smaller size, less revenue and small number of employees cannot operate with less information. There are many opportunities for these organizations however, additional tools are needed to generate potential value from these data. When dealing with value creation it is essential identify the main beneficiaries from value being created. The research's objective, still in development, is to create applications using open technology for information treatment and display to make them more explicit creating value in such open data. To validate the principal research's theoretical concept, this paper conducted a proof of concept with open data from a federal government agency that supports and finances investments in small and medium enterprises. The results proved to be possible to develop predictions about the possible investment expenditures for next year in each sector. |
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An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystemAnalyticsBig DataOpen DataR LanguageSmall and Medium EnterprisesWith the technologies proliferation for Internet, such as cloud computing, mobile devices, social media and the internet of things, small and medium enterprises, despite their smaller size, less revenue and small number of employees cannot operate with less information. There are many opportunities for these organizations however, additional tools are needed to generate potential value from these data. When dealing with value creation it is essential identify the main beneficiaries from value being created. The research's objective, still in development, is to create applications using open technology for information treatment and display to make them more explicit creating value in such open data. To validate the principal research's theoretical concept, this paper conducted a proof of concept with open data from a federal government agency that supports and finances investments in small and medium enterprises. The results proved to be possible to develop predictions about the possible investment expenditures for next year in each sector.School of Science Computing Department São Paulo State University-UNESPSchool of Science Computing Department São Paulo State University-UNESPUniversidade Estadual Paulista (Unesp)Albino, Joao Pedro [UNESP]2018-12-11T17:36:55Z2018-12-11T17:36:55Z2018-01-08info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject346-351http://dx.doi.org/10.1109/SAI.2017.8252125Proceedings of Computing Conference 2017, v. 2018-January, p. 346-351.http://hdl.handle.net/11449/17982410.1109/SAI.2017.82521252-s2.0-85046161086Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of Computing Conference 2017info:eu-repo/semantics/openAccess2024-04-23T16:11:19Zoai:repositorio.unesp.br:11449/179824Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:26:30.879908Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem |
title |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem |
spellingShingle |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem Albino, Joao Pedro [UNESP] Analytics Big Data Open Data R Language Small and Medium Enterprises |
title_short |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem |
title_full |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem |
title_fullStr |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem |
title_full_unstemmed |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem |
title_sort |
An approach to value creation in open data for small and medium-sized enterprises using 'R' ecosystem |
author |
Albino, Joao Pedro [UNESP] |
author_facet |
Albino, Joao Pedro [UNESP] |
author_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Albino, Joao Pedro [UNESP] |
dc.subject.por.fl_str_mv |
Analytics Big Data Open Data R Language Small and Medium Enterprises |
topic |
Analytics Big Data Open Data R Language Small and Medium Enterprises |
description |
With the technologies proliferation for Internet, such as cloud computing, mobile devices, social media and the internet of things, small and medium enterprises, despite their smaller size, less revenue and small number of employees cannot operate with less information. There are many opportunities for these organizations however, additional tools are needed to generate potential value from these data. When dealing with value creation it is essential identify the main beneficiaries from value being created. The research's objective, still in development, is to create applications using open technology for information treatment and display to make them more explicit creating value in such open data. To validate the principal research's theoretical concept, this paper conducted a proof of concept with open data from a federal government agency that supports and finances investments in small and medium enterprises. The results proved to be possible to develop predictions about the possible investment expenditures for next year in each sector. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-11T17:36:55Z 2018-12-11T17:36:55Z 2018-01-08 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/SAI.2017.8252125 Proceedings of Computing Conference 2017, v. 2018-January, p. 346-351. http://hdl.handle.net/11449/179824 10.1109/SAI.2017.8252125 2-s2.0-85046161086 |
url |
http://dx.doi.org/10.1109/SAI.2017.8252125 http://hdl.handle.net/11449/179824 |
identifier_str_mv |
Proceedings of Computing Conference 2017, v. 2018-January, p. 346-351. 10.1109/SAI.2017.8252125 2-s2.0-85046161086 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of Computing Conference 2017 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
346-351 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128513155268608 |