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Registro Completo |
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Biblioteca(s): |
Embrapa Pecuária Sudeste. |
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Data corrente: |
10/05/2023 |
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Data da última atualização: |
10/05/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
VILELA, F. DE A.; TIMES, V. C.; BERNARDI, A. C. de C.; FREITAS, A. DE P.; CIFERRI, R. R. |
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Afiliação: |
FLÁVIO DE ASSIS VILELA, Federal Institute of Goiás; VALÉRIA CESÁRIO TIMES, Federal University of Pernambuco; ALBERTO CARLOS DE CAMPOS BERNARDI, CPPSE; AUGUSTO DE PAULA FREITAS, Federal University of São Carlos; RICARDO RODRIGUES CIFERRI, Federal University of São Carlos. |
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Título: |
A non-intrusive and reactive architecture to support real-time ETL processes in data warehousing environments. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Heliyon, v. 9, n. 5, e15728, may 2023. |
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Páginas: |
25 p. |
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DOI: |
https://doi.org/10.1016/j.heliyon.2023.e15728 |
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Idioma: |
Inglês |
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Conteúdo: |
Nowadays, organizations are very interested to gather data for strategic decision-making. Data are disposable in operational sources, which are distributed, heterogeneous, and autonomous. These data are gathered through ETL processes, which occur traditionally in a pre-defined time, that is, once a day, once a week, once a month or in a specific period of time. On the other hand, there are special applications for which data needs to be obtained in a faster way and sometimes even immediately after the data are generated in the operation data sources, such as health systems and digital agriculture. Thus, the conventional ETL process and the disposable techniques are incapable of making the operational data delivered in real-time, providing low latency, high availability, and scalability. As our proposal, we present an innovative architecture, named Data Magnet, to cope with real-time ETL processes. The experimental tests performed in the digital agriculture domain using real and synthetic data showed that our proposal was able to deal in real-time with the ETL process. The Data Magnet provided great performance, showing an almost constant elapsed time for growing data volumes. Besides, Data Magnet provided significant performance gains over the traditional trigger technique. |
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Palavras-Chave: |
Data extraction; Data loading; Data warehouse; ETL; Real time. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1153634/1/NonIntrusiveReactive.pdf
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Marc: |
LEADER 02051naa a2200253 a 4500
001 2153634
005 2023-05-10
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.heliyon.2023.e15728$2DOI
100 1 $aVILELA, F. DE A.
245 $aA non-intrusive and reactive architecture to support real-time ETL processes in data warehousing environments.$h[electronic resource]
260 $c2023
300 $a25 p.
520 $aNowadays, organizations are very interested to gather data for strategic decision-making. Data are disposable in operational sources, which are distributed, heterogeneous, and autonomous. These data are gathered through ETL processes, which occur traditionally in a pre-defined time, that is, once a day, once a week, once a month or in a specific period of time. On the other hand, there are special applications for which data needs to be obtained in a faster way and sometimes even immediately after the data are generated in the operation data sources, such as health systems and digital agriculture. Thus, the conventional ETL process and the disposable techniques are incapable of making the operational data delivered in real-time, providing low latency, high availability, and scalability. As our proposal, we present an innovative architecture, named Data Magnet, to cope with real-time ETL processes. The experimental tests performed in the digital agriculture domain using real and synthetic data showed that our proposal was able to deal in real-time with the ETL process. The Data Magnet provided great performance, showing an almost constant elapsed time for growing data volumes. Besides, Data Magnet provided significant performance gains over the traditional trigger technique.
653 $aData extraction
653 $aData loading
653 $aData warehouse
653 $aETL
653 $aReal time
700 1 $aTIMES, V. C.
700 1 $aBERNARDI, A. C. de C.
700 1 $aFREITAS, A. DE P.
700 1 $aCIFERRI, R. R.
773 $tHeliyon$gv. 9, n. 5, e15728, may 2023.
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Embrapa Pecuária Sudeste (CPPSE) |
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