Data for good? Como as tecnologias de dados podem ajudar a contornar a crise do Covid

from MIT Technology Review Brasil · host TEC.INSTITUTE

A era do Covid-19 trouxe muitas incertezas à sociedade, mas, sem dúvida alguma, trouxe também novos olhares para as tecnologias de inteligência artificial, automação e analytics. Mais relevantes do que nunca, elas podem ser o diferencial competitivo que definirá como grandes empresas irão enfrentar – e superar - os desafios impostos pela pandemia. No episódio extra dessa semana, André Miceli, Carlos Aros e Rafael Coimbra conversam com Cassio Pantaleoni e Alexandre Sapia, do SAS, empresa especializada em analytics, para mergulhar mais a fundo nesse assunto e entender como a análise de dados pode trabalhar em prol da sociedade, em um exemplo palpável do chamado Data for Good. O podcast da MIT Technology Review Brasil é uma conversa semanal sobre os principais temas relacionados a tecnologia, inovação e negócios. Este episódio é patrocinado por SAS Brasil.

What this episode covers

A era do Covid-19 trouxe muitas incertezas à sociedade, mas, sem dúvida alguma, trouxe também novos olhares para as tecnologias de inteligência artificial, automação e analytics. Mais relevantes do que nunca, elas podem ser o diferencial competitivo que definirá como grandes empresas irão enfrentar – e superar - os desafios impostos pela pandemia. No episódio extra dessa semana, André Miceli, Carlos Aros e Rafael Coimbra conversam com Cassio Pantaleoni e Alexandre Sapia, do SAS, empresa especializada em analytics, para mergulhar mais a fundo nesse assunto e entender como a análise de dados pode trabalhar em prol da sociedade, em um exemplo palpável do chamado Data for Good. O podcast da MIT Technology Review Brasil é uma conversa semanal sobre os principais temas relacionados a tecnologia, inovação e negócios. Este episódio é patrocinado por SAS Brasil.

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Data for good? Como as tecnologias de dados podem ajudar a contornar a crise do Covid

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How long is this episode of MIT Technology Review Brasil?

This episode is 37 minutes long.

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This episode was published on July 3, 2020.

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