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Time series big data: a survey on data stream frameworks, analysis and algorithms.
Almeida, Ana; Brás, Susana; Sargento, Susana; Pinto, Filipe Cabral.
Afiliação
  • Almeida A; Instituto de Telecomunicações, Aveiro, Portugal.
  • Brás S; Departamento de Eletrónica, Telecomunicações e Informática, Universidade de Aveiro, Aveiro, Portugal.
  • Sargento S; Departamento de Eletrónica, Telecomunicações e Informática, Universidade de Aveiro, Aveiro, Portugal.
  • Pinto FC; IEETA, DETI, LASI, Universidade de Aveiro, Aveiro, Portugal.
J Big Data ; 10(1): 83, 2023.
Article em En | MEDLINE | ID: mdl-37274443
ABSTRACT
Big data has a substantial role nowadays, and its importance has significantly increased over the last decade. Big data's biggest advantages are providing knowledge, supporting the decision-making process, and improving the use of resources, services, and infrastructures. The potential of big data increases when we apply it in real-time by providing real-time analysis, predictions, and forecasts, among many other applications. Our goal with this article is to provide a viewpoint on how to build a system capable of processing big data in real-time, performing analysis, and applying algorithms. A system should be designed to handle vast amounts of data and provide valuable knowledge through analysis and algorithms. This article explores the current approaches and how they can be used for the real-time operations and predictions.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Big Data Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Portugal

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Big Data Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Portugal