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{"id":7614,"date":"2021-03-18T13:00:38","date_gmt":"2021-03-18T16:00:38","guid":{"rendered":"https:\/\/site.statplace.com.br\/?p=7614"},"modified":"2024-10-04T18:28:03","modified_gmt":"2024-10-04T18:28:03","slug":"quais-as-ferramentas-de-um-cientista-de-dados","status":"publish","type":"post","link":"https:\/\/site.statplace.com.br\/blog\/quais-as-ferramentas-de-um-cientista-de-dados\/","title":{"rendered":"Quais as ferramentas de um cientista de dados?"},"content":{"rendered":"\n

J\u00e1 falamos aqui no blog que o cientista de dados extrai valor dos dados<\/a> quando responde uma boa pergunta de neg\u00f3cios. E faz isso usando m\u00e9todos estruturados, conhecimentos em estat\u00edstica e desenvolvimento. Mas como acontece esse processo? Quais ferramentas um cientista de dados utiliza?<\/p>\n\n\n\n

No artigo de hoje vamos falar mais sobre as ferramentas, softwares e linguagens de programa\u00e7\u00e3o utilizados no trabalho com dados. E precisamos come\u00e7ar dizendo que existem softwares e linguagens de programa\u00e7\u00e3o como o R e o Python, bastante usadas hoje. \u00c9 sobre eles que vamos falar hoje. Mas existem outras formas de fazer uam boa an\u00e1lise de dados. Algumas pessoas usam Power BI,  Excel, SPSS ou SQL. Nesse caso a ferramenta usada pode at\u00e9 ajudar, mas o mais importante \u00e9 a capacidade anal\u00edtica, independente da plataforma.<\/p>\n\n\n\n

Dentro da comunidade de ci\u00eancia de dados existe uma discuss\u00e3o entre aqueles que preferem R e os que preferem Python. E a resposta correta para essa disputa de qual linguagem \u00e9 melhor \u00e9: ambas. As duas linguagens s\u00e3o excelentes para realizar o trabalho com dados.<\/p>\n\n\n\n

Cada uma tem suas vantagens e desvantagens, o ideal \u00e9 olhar para o projeto e avaliar qual usar em cada caso. O mais comum \u00e9 que um time escolha uma linguagem s\u00f3 e utilize na maioria dos projetos. Assim fica mais f\u00e1cil manter um projeto feito por muitas pessoas. E tamb\u00e9m permite treinar o time inteiro em uma \u00fanica linguagem. <\/p>\n\n\n\n

R e RStudio<\/h2>\n\n\n\n
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