Beyond technology: Management challenges in the Big Data era
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng por |
Título da fonte: | Revista de Administração de Empresas |
Texto Completo: | https://periodicos.fgv.br/rae/article/view/80770 |
Resumo: | The ability of organizations to produce, collect, manage, analyze, and transform data has increased rapidly over the past decade (Delen & Zolbanin, 2018). This has resulted in significant new challenges regarding how data can be leveraged for improving business decisions and how this new scenario changes business processes and operations (Vidgen, Shaw, & Grant, 2017). The widespread adoption of advanced analytical methods (e.g., machine learning) has attracted significant interest (Gupta, Deokar, Iyer, Sharda, & Schrader, 2018; Vassakis, Petrakis, & Kopanakis, 2018) particularly because the required data storage and methods can be accessed remotely through web-based interfaces such as cloud services. This has resulted in an increased belief that businesses must actively engage with this technology to remain competitive. However, this Red Queen scenario comes at a cost as collecting, curating, and managing large datasets requires expertise and dedicated staff, often consuming resources that do not contribute to core business activities. Consider the fact that there is an increasing role for data scientists and data engineers, among others, within organizations (Davenport & Patil, 2012). Roles such as Chief Data Officer (CDO) and Chief Analytics Officer (CAO)are now commonplace within most organizations. |
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Beyond technology: Management challenges in the Big Data eraAlém da tecnologia: Desafios gerenciais na era do Big DataThe ability of organizations to produce, collect, manage, analyze, and transform data has increased rapidly over the past decade (Delen & Zolbanin, 2018). This has resulted in significant new challenges regarding how data can be leveraged for improving business decisions and how this new scenario changes business processes and operations (Vidgen, Shaw, & Grant, 2017). The widespread adoption of advanced analytical methods (e.g., machine learning) has attracted significant interest (Gupta, Deokar, Iyer, Sharda, & Schrader, 2018; Vassakis, Petrakis, & Kopanakis, 2018) particularly because the required data storage and methods can be accessed remotely through web-based interfaces such as cloud services. This has resulted in an increased belief that businesses must actively engage with this technology to remain competitive. However, this Red Queen scenario comes at a cost as collecting, curating, and managing large datasets requires expertise and dedicated staff, often consuming resources that do not contribute to core business activities. Consider the fact that there is an increasing role for data scientists and data engineers, among others, within organizations (Davenport & Patil, 2012). Roles such as Chief Data Officer (CDO) and Chief Analytics Officer (CAO)are now commonplace within most organizations.A capacidade das organizações de produzir, coletar, gerenciar, analisar e transformar dados aumentou rapidamente na última década (Delen & Zolbanin, 2018). Isso gerou novos desafiossignificativos em relação a como os dados podem ser aproveitados para melhorar as decisões de negócios e como esse novo cenário altera os processos e as operações de negócios (Vidgen, Shaw, & Grant, 2017). A adoção generalizada de métodos analíticos avançados (por exemplo, aprendizado de máquina) tem atraído bastante interesse (Gupta, Deokar, Iyer, Sharda, & Schrader, 2018; Vassakis, Petrakis, & Kopanakis, 2018), principalmente porque o armazenamento de dados e os métodos necessários podem ser acessados remotamente por meio de interfaces baseadas na web, como serviços em nuvem. Isso gerou uma crença crescente de que as empresas devem envolver-se ativamente com essa tecnologia para se manterem competitivas. No entanto, esse cenário de corrida da Rainha Vermelha (que pressupõe um desenvolvimento contínuo por parte das empresas) tem um custo, pois a coleta, a curadoria e o gerenciamento de grandes conjuntos de dados requerem experiência e uma equipe dedicada, o que, muitas vezes, consome recursos que não contribuem para as principais atividades do negócio. É preciso considerar também que cientistas de dados e engenheiros de dados, entre outros, cada vez mais exercem um papel relevante dentro das organizações (Davenport & Patil, 2012). Cargos como Chief Data Officer (CDO) e Chief Analytics Officer (CAO) agora são comuns na maioria das organizações.RAE - Revista de Administracao de Empresas RAE - Revista de Administração de EmpresasRAE-Revista de Administração de Empresas2019-12-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado por Paresapplication/pdfapplication/pdfhttps://periodicos.fgv.br/rae/article/view/8077010.1590/S0034-759020190603RAE - Revista de Administracao de Empresas ; Vol. 59 No. 6 (2019): november-december; 375-378RAE - Revista de Administração de Empresas; Vol. 59 Núm. 6 (2019): november-december; 375-378RAE-Revista de Administração de Empresas; v. 59 n. 6 (2019): novembro-dezembro; 375-3782178-938X0034-7590reponame:Revista de Administração de Empresasinstname:Fundação Getulio Vargas (FGV)instacron:FGVengporhttps://periodicos.fgv.br/rae/article/view/80770/77144https://periodicos.fgv.br/rae/article/view/80770/77145Copyright (c) 2019 RAE - Revista de Administração de Empresasinfo:eu-repo/semantics/openAccessFrancisco, Eduardo de RezendeKugler, José LuizKang, Soong MoonSilva, RicardoWhigham, Peter Alexander2020-01-09T19:29:47Zoai:ojs.periodicos.fgv.br:article/80770Revistahttps://rae.fgv.br/raeONGhttps://old.scielo.br/oai/scielo-oai.phprae@fgv.br||ilda.fontes@fgv.br||raeredacao@fgv.br2178-938X0034-7590opendoar:2024-03-06T13:06:04.113724Revista de Administração de Empresas - Fundação Getulio Vargas (FGV)true |
dc.title.none.fl_str_mv |
Beyond technology: Management challenges in the Big Data era Além da tecnologia: Desafios gerenciais na era do Big Data |
title |
Beyond technology: Management challenges in the Big Data era |
spellingShingle |
Beyond technology: Management challenges in the Big Data era Francisco, Eduardo de Rezende |
title_short |
Beyond technology: Management challenges in the Big Data era |
title_full |
Beyond technology: Management challenges in the Big Data era |
title_fullStr |
Beyond technology: Management challenges in the Big Data era |
title_full_unstemmed |
Beyond technology: Management challenges in the Big Data era |
title_sort |
Beyond technology: Management challenges in the Big Data era |
author |
Francisco, Eduardo de Rezende |
author_facet |
Francisco, Eduardo de Rezende Kugler, José Luiz Kang, Soong Moon Silva, Ricardo Whigham, Peter Alexander |
author_role |
author |
author2 |
Kugler, José Luiz Kang, Soong Moon Silva, Ricardo Whigham, Peter Alexander |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Francisco, Eduardo de Rezende Kugler, José Luiz Kang, Soong Moon Silva, Ricardo Whigham, Peter Alexander |
description |
The ability of organizations to produce, collect, manage, analyze, and transform data has increased rapidly over the past decade (Delen & Zolbanin, 2018). This has resulted in significant new challenges regarding how data can be leveraged for improving business decisions and how this new scenario changes business processes and operations (Vidgen, Shaw, & Grant, 2017). The widespread adoption of advanced analytical methods (e.g., machine learning) has attracted significant interest (Gupta, Deokar, Iyer, Sharda, & Schrader, 2018; Vassakis, Petrakis, & Kopanakis, 2018) particularly because the required data storage and methods can be accessed remotely through web-based interfaces such as cloud services. This has resulted in an increased belief that businesses must actively engage with this technology to remain competitive. However, this Red Queen scenario comes at a cost as collecting, curating, and managing large datasets requires expertise and dedicated staff, often consuming resources that do not contribute to core business activities. Consider the fact that there is an increasing role for data scientists and data engineers, among others, within organizations (Davenport & Patil, 2012). Roles such as Chief Data Officer (CDO) and Chief Analytics Officer (CAO)are now commonplace within most organizations. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-05 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Avaliado por Pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.fgv.br/rae/article/view/80770 10.1590/S0034-759020190603 |
url |
https://periodicos.fgv.br/rae/article/view/80770 |
identifier_str_mv |
10.1590/S0034-759020190603 |
dc.language.iso.fl_str_mv |
eng por |
language |
eng por |
dc.relation.none.fl_str_mv |
https://periodicos.fgv.br/rae/article/view/80770/77144 https://periodicos.fgv.br/rae/article/view/80770/77145 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2019 RAE - Revista de Administração de Empresas info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2019 RAE - Revista de Administração de Empresas |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
RAE - Revista de Administracao de Empresas RAE - Revista de Administração de Empresas RAE-Revista de Administração de Empresas |
publisher.none.fl_str_mv |
RAE - Revista de Administracao de Empresas RAE - Revista de Administração de Empresas RAE-Revista de Administração de Empresas |
dc.source.none.fl_str_mv |
RAE - Revista de Administracao de Empresas ; Vol. 59 No. 6 (2019): november-december; 375-378 RAE - Revista de Administração de Empresas; Vol. 59 Núm. 6 (2019): november-december; 375-378 RAE-Revista de Administração de Empresas; v. 59 n. 6 (2019): novembro-dezembro; 375-378 2178-938X 0034-7590 reponame:Revista de Administração de Empresas instname:Fundação Getulio Vargas (FGV) instacron:FGV |
instname_str |
Fundação Getulio Vargas (FGV) |
instacron_str |
FGV |
institution |
FGV |
reponame_str |
Revista de Administração de Empresas |
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Revista de Administração de Empresas |
repository.name.fl_str_mv |
Revista de Administração de Empresas - Fundação Getulio Vargas (FGV) |
repository.mail.fl_str_mv |
rae@fgv.br||ilda.fontes@fgv.br||raeredacao@fgv.br |
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