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Big Data Big Data Processamento Analítico de Dados Profa. Dra. Cristina Dutra de Aguiar Ciferri

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Big Data

Processamento Analítico de Dados Profa. Dra. Cristina Dutra de Aguiar Ciferri

Big Data

Imagem: https://students.washington.edu/bits/club/wp-content/uploads/2014/05/Big-data.Red_.jpg

Big Data

Definição: Modelo de 3Vs

Big Data

Variedade

Volume

Velocidade

gigantesca quantidade de dados

captura e disponibilidade de

um gigantesco volume de dados em um

pequeno intervalo de tempo

dados podem ser de qualquer tipo (estruturados,

semiestruturados, não estruturados)

Chen, M.; Mao, S.; Liu, Y. Big Data: A Survey. Mobile Network Applications, v. 19, p. 171-209, 2014.

Big Data

Definição: Modelo de 4Vs

Big Data

Variedade

Volume

Velocidade

quão confiáveis são os dados

Veracidade

Dong, X. L.; Srivastava, D. Big Data Integration. Proceedings of the VLDB Endowment, v. 6, n. 11, p. 1188-1189, 2013.

Big Data

Definição: Modelo de 5Vs

Big Data

Variedade

Volume

Velocidade

os dados devem ter importância

Veracidade

Valor

Sharma, S.; Mangat, V. Technology and Trends to Handle Big Data: Survey. In: Proceedings of the Fifth International Conference on Advanced Computing & Communication Technologies, p. 266-271, 2015.

Big Data

•  Dados possuem informações valiosas •  Exemplos

– análise de navegação e reviews de usuários

•  recomendação personalizada de produtos – análise de mensagens de redes sociais

Big Data

Imagem: http://www.ufmg.br/online/arquivos/anexos/Portal_Observatorio_Dengue.JPG

Observatório da Dengue

Aumento de mensagens

relacionadas ao termo “dengue” em uma

região pode indicar um possível surto

•  Monitoramento de mensagens de redes sociais – desenvolvido por pesquisadores da UFMG

Big Data

NetFlix

Imagens: http://pt.slideshare.net/laodias/os-cinco-vs-do-big-data http://img.vivaolinux.com.br/imagens/dicas/comunidade/netflix.png

•  Análise –  Kevin Spacey e David Fincher:

grande aceitação –  mesmos usuários: gostam de

thrillers políticos

Big Data

Desafios

•  Uso de ambientes computacionais com grande capacidade de armazenamento e processamento – clusters de computadores – computação em nuvem

•  Uso de sistemas de arquivos distribuídos – HDFS

Big Data

Desafios

•  Emprego de paradigmas de programação paralela e distribuída –  framework MapReduce –  framework Spark

•  Uso de bancos de dados NoSQL – diferentes modelos de dados

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