Benchmarking business analytics techniques in Big Data

Technological developments and the growing dependence of organizations and society in the world of the internet led to the growth and variety of data. This growth and variety have become a challenge to the traditional techniques of Business Analytics. In this project, we conducted a benchmarking pro...

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Detalhes bibliográficos
Autor principal: Oliveira, Catia (author)
Outros Autores: Guimarães, Tiago André Saraiva (author), Portela, Filipe (author), Santos, Manuel (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2019
Assuntos:
Texto completo:http://hdl.handle.net/1822/67912
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/67912
Descrição
Resumo:Technological developments and the growing dependence of organizations and society in the world of the internet led to the growth and variety of data. This growth and variety have become a challenge to the traditional techniques of Business Analytics. In this project, we conducted a benchmarking process that aimed to assess the performance of some Data Mining tools, like RapidMiner, in Big Data environment. Firstly, was analyzed a study where a group of Data Mining tools are evaluated and determined what is the best Data Mining tool, according to the evaluation criteria. After that, the best two tools considered in the study are analyzed regarding their ability to analyze data in a Big Data environment. Finally, studies were carried out on the evaluations of the RapidMiner and KNIME tools for their performance in the Big Data environment.