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aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"overview","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-edfd06b07e","additionalClasses":"headline-decoration","type":"heading2","lines":["Visão geral"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-9f54c7e60f","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EA maioria das pessoas não ousaria viajar sem ter um app de GPS ou até mesmo um mapa. Imagine viajar de carro por países onde você nunca esteve antes, lugares totalmente desconhecidos, possivelmente com estradas difíceis e outros perigos, sem nada para orientar você, exceto as placas de trânsito e o seu instinto. Da mesma forma, empresas não podem agir apenas com base em votos de confiança e suposições. Todas as organizações precisam de dados para orientar suas decisões, campanhas e otimização de negócios, independentemente do setor ou tamanho. É aqui que entra a \u003Ca href=\"https://www.snowflake.com/pt_br/product/analytics/\"\u003Eanálise de dados\u003C/a\u003E.\u003C/p\u003E\n\u003Cp\u003ECom a análise de dados, as empresas descobrem a inteligência mais importante de que precisam para evoluir, crescer e melhorar tanto para seus clientes quanto para as equipes internas. Sem isso, elas perdem terreno para os concorrentes, que trabalham para aumentar a participação no mercado, elaborando movimentos inteligentes e planos cuidadosos apoiados por pesquisas.\u003C/p\u003E\n\u003Cp\u003ENeste guia, veremos os diferentes tipos de análise de dados e suas vantagens, alguns casos de uso mais comuns e as principais ferramentas de análise de dados para ajudar você a começar a implementar dados em suas decisões e análises de negócios.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"}},":itemsOrder":["title_v2","text"]},"container_copy_copy_":{"columnClassNames":{"container_copy_copy__480869401":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__373061683":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1444615495":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__222865509":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1413360324":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy_":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__455068363":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__659376865":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1500909857":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1978652079":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"rel","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"container_copy_copy":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"what","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-b208db50e1","additionalClasses":"headline-decoration","type":"heading2","lines":["O que é análise de dados?"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-7a0fe221b2","text":"\u003Cp\u003EA análise de dados é um processo que consistem em de examinar, coletar e análise de dados brutos para identificar padrões e chegar a conclusões. Análises de dados auxiliam o crescimento dos negócios, promovendo a tomada de decisões com base em informações e ajudando as organizações a melhorar o desempenho de todas as equipes. \u003C/p\u003E\n\u003Cp\u003EVárias ferramentas e técnicas são usadas para reunir e extrair insights de dados, como planilhas, \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-lake-vs-data-warehouse-vs-data-mart/\"\u003Edata warehouses\u003C/a\u003E e linguagens de programação. Qualquer tipo de informação pode ser verificada usando essas técnicas, como métricas de mídias sociais, \u003Ca href=\"https://www.snowflake.com/pt_br/solutions/industries/healthcare-and-life-sciences/\"\u003Ehistóricos de saúde de pacientes\u003C/a\u003E, números reduzidos de estoque e muito mais. Independente do tamanho da organização ou se ela tem analistas de dados dedicados para analisar os dados, qualquer equipe pode usar as principais ferramentas de análise de dados para descobrir as informações de que precisa. Uma vantagem enorme da análise de dados é que ela pode reunir um grande volume de informações para revelar tendências e padrões que de outra forma ficariam perdidos no meio de todo o ruído digital.\u003C/p\u003E\n\u003Cp\u003EDesde empresas de jogos interessadas em analisar o comportamento dos jogadores, até um \u003Ca href=\"https://www.snowflake.com/pt_br/solutions/industries/financial-services/\"\u003Ebanco\u003C/a\u003E acompanhando o comportamento do cliente para procurar possíveis sinais de fraude, até varejistas prevendo quando um cliente vai realizar sua próxima compra, a análise de dados possibilita às empresas criar uma experiência personalizada, reduzir riscos e aumentar a fidelidade à marca.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"]},"container_copy_copy_":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"a","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-b1cdfa0bf0","additionalClasses":"headline-decoration","type":"heading2","lines":["Tipos de análise de dados"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-e47209e896","text":"\u003Cp\u003EExistem quatro tipos de análises de dados, que se complementam entre si: desde compreender eventos passados até influenciar resultados futuros por meio de insights e recomendações baseados em dados.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Análise de dados descritiva: o que aconteceu?\u003C/h4\u003E\n\u003Cp\u003EEsse tipo de análise resume dados históricos para entender o que ocorreu em um determinado período de tempo. Por exemplo, se houve um aumento no número de “likes” em suas publicações de mídias sociais, um número maior de transações em jogo ou uma redução nas vendas de produtos trimestrais. A análise descritiva é o nível mais básico de análise.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Análise de dados diagnóstica: por que isso aconteceu?\u003C/h4\u003E\n\u003Cp\u003EÉ nesta etapa que o processo se complica um pouco mais, mas também se torna mais interessante. O foco da análise de dados diagnóstica está em determinar as causas desses eventos anteriores. Ela requer a combinação de entradas de dados e elaboração de hipóteses. Usamos as hashtags certas para aumentar a visibilidade da publicação? Talvez a promoção por tempo limitado durante o jogo tenha incentivado o aumento das vendas?\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Análise de dados preditiva: o que acontecerá?\u003C/h4\u003E\n\u003Cp\u003EAgora que você já entendeu o quê e o porquê, precisa começar a planejar os passos seguintes. A \u003Ca href=\"https://www.snowflake.com/en/fundamentals/predictive-analytics-marketing/\"\u003Eanálise de dados preditiva\u003C/a\u003E ajuda você a descobrir o que é mais provável de acontecer no futuro. Seu cliente tende a comprar produtos para gatos todos os meses nessa mesma época, então há uma alta probabilidade de que ele esteja prestes a fazer outra compra. O cliente do seu banco tem um histórico de pagamento pontual de faturas, então é provável que ele também seja confiável em relação às prestações de empréstimos.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Análise de dados prescritiva: o que fazer?\u003C/h4\u003E\n\u003Cp\u003ENesta etapa, é onde você pode começar a colocar todos os dados e informações coletados e analisados em recomendações para seu próximo curso de ação. Nos últimos meses sua marca teve um grande aumento de vendas, e o estoque do último produto lançado se esgotou em apenas alguns minutos após o lançamento. Então, para o próximo lançamento, sua empresa precisa configurar um sistema de encomendas antecipadas para melhorar a satisfação dos clientes.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"]},"container_copy_copy__1444615495":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"use","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-7559b2c50f","additionalClasses":"headline-decoration","type":"heading2","lines":["Benefícios da análise de dados"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-9463567848","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003ETer uma estratégia sólida de análise de dados pode ter efeitos transformadores em sua empresa, dando à sua organização uma melhor visibilidade do que está indo bem e do que ainda precisa ser melhorado. Ela conecta o saber e o fazer, permitindo às equipes otimizar a eficiência e a satisfação do cliente. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Processo decisório mais fundamentado\u003C/h4\u003E\n\u003Cp\u003ESem adivinhações ou suposições. Tome decisões “data-driven”, com base em provas e padrões identificados em conjuntos de dados históricos para obter resultados mais precisos e confiáveis.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Maior eficiência operacional\u003C/h4\u003E\n\u003Cp\u003ETer o conhecimento já é meio caminho andado, como dizem, e a análise de dados fornece os insights práticos que podem apontar ineficiências operacionais, gargalos e oportunidades de melhoria em toda a organização. Isso dá às empresas as informações necessárias para simplificar processos, reduzir custos, melhorar a produtividade e eliminar ou aprimorar estratégias que não estejam mais funcionando.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Redução de riscos\u003C/h4\u003E\n\u003Cp\u003ECom a evolução constante e o aumento da frequência das fraudes, as empresas devem permanecer atentas a agentes mal-intencionados. A análise de dados permite identificar ameaças e anomalias, de modo proativo, tornando mais fácil para as organizações elaborarem estratégias direcionadas de redução de riscos com o uso de IA e aprendizado de máquina.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Conhecimento mais detalhado sobre o cliente\u003C/h4\u003E\n\u003Cp\u003EA análise de dados fornece às empresas os principais dados e insights necessários para personalizar a experiência dos clientes, melhorar seus produtos e serviços e aumentar a satisfação e a fidelidade dos clientes. Essa é uma imensa vantagem competitiva que ajuda a melhorar não apenas a retenção de clientes, mas também a conquistar novos clientes, garantindo o crescimento geral da empresa.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"]},"container_copy_copy__1978652079":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"benefits","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-74703bf2ed","additionalClasses":"headline-decoration","type":"heading2","lines":["Etapas da análise de dados"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-0ee2b75f95","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EEmbora ter um vasto volume de dados seja uma boa ideia, existem etapas que você deve seguir primeiro para transformá-los de dados em estado bruto para dados que possam fornecer insights significativos e utilizáveis. Um típico projeto de análise de dados requer trabalhar durante o ciclo de vida da análise de dados: definindo o objetivo, coletando os dados, limpando e preparando os dados e analisando-os. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Definir o objetivo\u003C/h4\u003E\n\u003Cp\u003EO que exatamente sua equipe espera obter dos dados que está coletando? Que processo ou operação você está tentando otimizar? Que campanha você está apoiando? Investir tempo e recursos reunindo um grande volume de dados não será útil se você não tiver metas claras e definidas. Descreva em detalhes o que você deseja alcançar. Dessa forma, você pode determinar os dados de que você precisa e como eles devem ser agrupados e separados.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Coletar os dados\u003C/h4\u003E\n\u003Cp\u003EAgora que você já sabe exatamente o que procura, os analistas de dados da sua empresa podem coletar dados relevantes para apoiar os objetivos. Os dados podem ser de qualquer tipo, desde tráfego em seu site em um determinado período de tempo, pesquisas de clientes, estatísticas de engajamento de mídias sociais, dados transacionais, avaliação de risco e muito mais.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Limpar e preparar os dados\u003C/h4\u003E\n\u003Cp\u003ELimpe e examine os dados em busca de erros, inconsistências e valores atípicos que possam afetar a confiabilidade e a usabilidade do conjunto de dados. Em seguida, organize-os para facilitar a análise. As planilhas são ideais para conjuntos de dados menores. No entanto, elas ficam lentas e complicadas ao lidar com conjuntos de dados maiores. As ferramentas de \u003Ca href=\"https://www.snowflake.com/pt_br/fundamentals/ai-for-business-intelligence/\"\u003Einteligência de mercado\u003C/a\u003E (business intelligence, BI) são ideais para visualização de dados e dashboards, enquanto \u003Ca href=\"https://www.snowflake.com/pt_br/product/analytics/\"\u003Ebancos de dados e data warehouses\u003C/a\u003E são necessários para conjuntos de dados muito grandes.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Analisar os dados\u003C/h4\u003E\n\u003Cp\u003EAgora, que você possui seu conjunto de dados limpo e preparado, chegou a hora de aprofundar as análises, usando técnicas lógicas e estatísticas para descobrir padrões, relações e tendências. Lembra dos tipos de análise de dados que discutimos antes? É nesta etapa que os analistas de dados adotam esses métodos para entender o quê e o porquê de seus dados e planejar as próximas etapas. \u003C/p\u003E\n\u003Cp\u003EAs planilhas e as versões gratuitas das ferramentas de BI são recursos comuns para analisar pequenos conjuntos de dados e, normalmente, são usadas por equipes menores, que talvez nem tenham um analista de dados dedicado no quadro de pessoal. No nível corporativo, os serviços na nuvem e as estruturas de processamento de big data lidam com conjuntos de dados intermediários de grandes volumes, muitas vezes em conjunto com plataformas de BI com diversos recursos, para produzir visualizações e relatórios detalhados.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"]},"container_copy_copy__455068363":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"how","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-30498367d2","additionalClasses":"headline-decoration","type":"heading2","lines":["Técnicas de análise de dados"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-567391369d","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EDe modo geral, as técnicas de análise de dados se encaixam nas categorias de aprendizado supervisionado e não supervisionado. Técnicas supervisionadas utilizam dados rotulados para fazer previsões, enquanto técnicas sem supervisão se concentram em identificar padrões em dados não rotulados.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAnálise de regressão\u003C/h4\u003E\n\u003Cp\u003EEssa é uma técnica de aprendizado supervisionado usada para prever um valor numérico contínuo com base em uma ou mais variáveis independentes. Em outras palavras, é um método estatístico adotado para entender a relação entre uma variável dependente e uma ou mais variáveis independentes, combinando uma linha ou curva aos dados. Essa técnica ajuda a determinar as variáveis que terão impacto.\u003C/p\u003E\n\u003Cp\u003EUma das principais perguntas que a \u003Ca href=\"https://hbr.org/2015/11/a-refresher-on-regression-analysis\"\u003Eanálise de regressão\u003C/a\u003E pode responder é \"Quanto ou quantos?\", o que ajuda as empresas a determinar quais fatores importam mais e menos.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAnálise de classificação\u003C/h4\u003E\n\u003Cp\u003EA análise de classificação responde à pergunta: \"A que classe ou categoria isto pertence?\". Ela é uma ferramenta poderosa para entender as informações e tomar decisões fundamentadas.\u003C/p\u003E\n\u003Cp\u003EEssa técnica de aprendizado supervisionado é usada para classificar e categorizar dados em grupos, treinando um modelo de classificação e, em seguida, fornecendo novos dados para prever a que categoria ele pertence. Em essência, a \u003Ca href=\"https://www.indicative.com/resource/classification-analysis/\"\u003Eanálise de classificação\u003C/a\u003E consiste em usar dados já rotulados no passado para ensinar um modelo a categorizar corretamente dados novos e não rotulados.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EAnálise de clustering\u003C/h4\u003E\n\u003Cp\u003EDiferente das duas técnicas anteriores, a \u003Ca href=\"https://www.qualtrics.com/experience-management/research/cluster-analysis/\"\u003Eanálise de clustering\u003C/a\u003E é uma técnica de aprendizado sem supervisão usada para agrupar pontos de dados semelhantes em clusters. Não há rótulos ou categorias predefinidas. O algoritmo descobre os agrupamentos dentro dos dados. A análise de clustering responde à perguntas: \"Como podemos agrupar esses dados?\"\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"]},"container_copy_copy__222865509":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"ai","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-1767275b73","additionalClasses":"headline-decoration","type":"heading2","lines":["Casos de uso de análise de dados"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-7d47e8b83f","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EComo mencionamos no início deste guia, todos os setores podem se beneficiar da análise de dados, e empresas de todos os tamanhos estão obtendo vantagem competitiva ao utilizar seus próprios dados para otimizar, evoluir e crescer. Vamos analisar três setores: \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003Evarejo\u003C/a\u003E, saúde e setor financeiro, para ver como eles, em geral, incorporam análise de dados aos seus fluxos de trabalho e processos.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EVarejo\u003Cbr\u003E\n \u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003EPersonalização de anúncios: os varejistas podem usar os dados coletados de cada cliente, como históricos de compras, dados demográficos e comportamentais, para personalizar os emails e as promoções de mídias sociais que enviam a esses clientes. Criar uma experiência de compra personalizada ajuda a desenvolver a fidelidade da marca e aumentar o percentual total de gasto do cliente.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EGestão de estoque de varejo online: para garantir que os níveis do estoque possam atender à demanda dos clientes, os varejistas online analisam comportamentos de compra anteriores dos clientes, níveis de estoque e dados públicos e de terceiros. Manter as prateleiras digitais bem abastecidas aumenta a retenção de clientes e evita que eles busquem alternativas em outros lugares para obter o que precisam.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ESegurança integral: é indispensável que as lojas físicas eliminem riscos que possam prejudicar clientes ou funcionários. Analisar vários pontos de dados, como relatórios de incidentes e registros de treinamento de segurança, e utilizar os quatro tipos de análise de dados, pode ajudar as autoridades a desenvolver melhor treinamento de segurança para os funcionários a fim de reduzir a ocorrência de incidentes.\u003Cbr\u003E\n \u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch4\u003ESaúde\u003Cbr\u003E\n \u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003EPrevisão de doenças: a análise de dados preditiva usa dados de pacientes, como estilo de vida, informação genética e histórico médico, para identificar pacientes com alto risco de desenvolver determinadas doenças. Isso ajuda os médicos a desenvolver tratamentos personalizados e iniciar cuidados preventivos para evitar a doença.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EAlocação de recursos: os hospitais podem usar dados, como o atendimento periódico em prontos-socorros, para prever os níveis de admissão dos pacientes e otimizar a equipe e os recursos disponíveis para atender às necessidades dele, reduzindo o tempo de espera e aumentando a satisfação do paciente.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EDetecção de fraudes: a análise de dados pode ajudar hospitais, farmácias e seguradoras a prevenir fraudes, analisando padrões de faturamento, uso de receita médica e ocorrências de sinistros de seguro para identificar anomalias e transações não autorizadas.\u003Cbr\u003E\n \u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch4\u003ESetor financeiro\u003Cbr\u003E\n \u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003EGestão de riscos: os bancos podem analisar uma variedade de dados de clientes, incluindo hábitos de gastos, estabilidade da receita e histórico de pagamento, para determinar a credibilidade de um indivíduo.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EPrevisão de perda de clientes: se alguns dados (como falta atividade bancária recente ou taxas elevadas) apontarem que talvez o cliente venha a fechar a conta, o banco pode oferecer, de forma proativa, serviços ou incentivos para mantê-lo, como uma melhor taxa de rendimento.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ETrading algorítmico e análise de mercado: as empresas de trading de alta frequência usam algoritmos complexos para analisar dados de mercado, identificar oportunidades e tendências de mercado e realizar negociações em segundos.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"]},"container_copy_copy__1413360324":{"columnClassNames":{"title_v2_copy":"aem-GridColumn aem-GridColumn--default--12","text_copy":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"tools","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2_copy":{"id":"title-v2-8b665c1cf2","additionalClasses":"headline-decoration","type":"heading2","lines":["Principais ferramentas de análise de dados"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text_copy":{"id":"text-3f04ec515e","additionalClasses":"list--blue-bullets","text":"\u003Cul\u003E\n\u003Cli\u003EPlanilhas: Microsoft Excel e Google Sheets.\u003C/li\u003E\n\u003Cli\u003EFerramentas de BI (Business intelligence): Tableau, Microsoft Power BI.\u003C/li\u003E\n\u003Cli\u003ELinguagens de programação: Python, R, SQL.\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2_copy","text_copy"]},"container_copy_copy__659376865":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"conclusion","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-23bda727e5","additionalClasses":"headline-decoration","type":"heading2","lines":["Conclusão"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-55ad4d89d4","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EPraticamente em qualquer setor, a análise de dados é indispensável para se obter uma vantagem competitiva. O processo decisório baseado em dados gera eficiências significativas ao otimizar processos internos, atualizar a experiência do cliente, aumentar a fidelidade da marca e, no caso do setor de saúde, melhorar o bem-estar do paciente. \u003C/p\u003E\n\u003Cp\u003EO volume de dados continua a crescer a taxas surpreendentes, aumentando a complexidade dos desafios de análise de dados. Ao mesmo tempo, as ferramentas e as técnicas, incluindo aplicações avançadas de IA, oferecem novas maneiras de interagir com os dados para obter insights de alto valor. Espera-se que o crescente campo da análise de dados continue sendo parte integrante do sucesso na era digital.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"]},"container_copy_copy__1500909857":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","simple_snowflake_acc":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"faq","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-a07803b114","additionalClasses":"headline-decoration","type":"heading2","lines":["Perguntas frequentes sobre análise de dados"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"simple_snowflake_acc":{"id":"simple-snowflake-accordion-876e33f7f6","additionalClasses":"list--blue-bullets","showDivider":false,"accordionItemsList":[{"title":"Quais são os melhores cursos de análise de dados?","richText":"\u003Cp\u003EOrçamentos, estilos de aprendizado e objetivos de carreira são diferentes para cada um. No entanto, os melhores cursos de análise de dados são aqueles que fornecem um bom conhecimento em habilidades básicas, como linguagens de programação e ferramentas de visualização de dados. Existem muitos cursos online gratuitos em plataformas como Coursera e DataCamp que oferecem uma introdução à análise de dados. A Forbes compilou \u003Ca href=\"https://www.forbes.com/advisor/education/certifications/best-data-analytics-certifications/\"\u003Euma lista das melhores certificações de análise de dados online\u003C/a\u003E. Na Snowflake, oferecemos a certificação \u003Ca href=\"https://learn.snowflake.com/en/certifications/snowpro-advanced-dataanalyst/?pdf_name=SnowProDataAnalystStudyGuide\"\u003ESnowPro® Advanced: Data Analyst\u003C/a\u003E, um treinamento voltado para desenvolver habilidades e obter o conhecimento das técnicas avançadas usadas para aplicar princípios de análise de dados usando o Snowflake.\u003C/p\u003E\n"},{"title":"Que ferramentas são usadas para analisar grandes volumes de dados?","richText":"\u003Cp\u003EExistem várias ferramentas especializadas que podem lidar com grandes volumes de dados, processá-los rapidamente e extrair insights significativos. Veja alguns exemplos a seguir:\u003Cbr\u003E\n \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003EEstruturas de big data: \u003Ca href=\"https://www.snowflake.com/pt_br/product/features/snowpark/\"\u003ESnowflake Snowpark\u003C/a\u003E, \u003Ca href=\"https://hadoop.apache.org/\"\u003EApache Hadoop\u003C/a\u003E, \u003Ca href=\"https://spark.apache.org/\"\u003EApache Spark\u003C/a\u003E.\u003C/li\u003E\n\u003Cli\u003EData warehouses baseados em nuvem: \u003Ca href=\"https://cloud.google.com/bigquery?utm_source=google&utm_medium=cpc&utm_campaign=na-US-all-en-dr-bkws-all-all-trial-e-dr-1710134&utm_content=text-ad-none-any-DEV_c-CRE_772298885512-ADGP_Hybrid+%7C+BKWS+-+EXA+%7C+Txt-Data+Analytics-Data+Analytics-BigQuery-KWID_43700082585516178-kwd-63326440124&utm_term=KW_google%20bigquery-ST_google+bigquery&gclsrc=aw.ds&gad_source=1&gad_campaignid=22970352687&gclid=Cj0KCQjwoP_FBhDFARIsANPG24P3VZl3_a-liWj18JKg9cBt96oy0h9fSeV7h9G4GzXW5-1YxrW6tdUaAsoCEALw_wcB\"\u003EGoogle BigQuery\u003C/a\u003E, \u003Ca href=\"https://aws.amazon.com/pm/redshift/?trk=a136dbb3-ff50-468b-9a66-852dc1ca985b&sc_channel=ps&ef_id=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB:G:s&s_kwcid=AL!4422!3!651751058853!e!!g!!amazon%20redshift!19852662155!145019245577&gad_campaignid=19852662155&gbraid=0AAAAADjHtp_w47gFWrFMuAm5btwOo9ScF&gclid=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB\"\u003EAmazon Redshift\u003C/a\u003E e \u003Ca href=\"https://www.snowflake.com/pt_br/product/analytics/\"\u003ESnowflake\u003C/a\u003E.\u003C/li\u003E\n\u003Cli\u003EFerramentas de visualização e BI: \u003Ca href=\"https://www.tableau.com/\"\u003ETableau\u003C/a\u003E, \u003Ca href=\"https://www.microsoft.com/en-us/power-platform/products/power-bi\"\u003EMicrosoft Power BI\u003C/a\u003E.\u003C/li\u003E\n\u003Cli\u003ELinguagens de programação e bibliotecas: \u003Ca href=\"https://www.python.org/\"\u003EPython\u003C/a\u003E, \u003Ca href=\"https://www.r-project.org/\"\u003ER\u003C/a\u003E, \u003Ca href=\"https://www.coursera.org/specializations/learn-sql-basics-data-science/paidmedia?utm_medium=sem&utm_source=gg&utm_campaign=b2c_namer_learn-sql-basics-data-science_ucdavis_ftcof_specializations_px_dr_bau_gg_sem_pr-bd_us-ca_en_m_hyb_24-12_x&campaignid=20743946861&adgroupid=154886907309&device=c&keyword=sql&matchtype=b&network=g&devicemodel=&creativeid=679514232408&assetgroupid=&targetid=kwd-10206160&extensionid=&placement=&gad_source=1&gad_campaignid=20743946861&gbraid=0AAAAADdKX6azVKefwfYb2NyuzsKTgMGOJ&gclid=Cj0KCQjwoP_FBhDFARIsANPG24PZTNLiGUpmlyl3WDAV8k-_Yop5rD7fxGmgImdMCl0YROUq1DUPB04aAsUhEALw_wcB\"\u003ESQL\u003C/a\u003E.\u003C/li\u003E\n\u003C/ul\u003E\n"},{"title":"Qual é um exemplo de análise de dados?","richText":"\u003Cp\u003ESegmentação de clientes no \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003Esetor de varejo\u003C/a\u003E. Os \u003Ca href=\"https://www.snowflake.com/pt_br/solutions/industries/retail-consumer-goods/\"\u003Evarejistas\u003C/a\u003E podem usar o grande volume de dados de clientes que eles coletam para agrupar os clientes em diferentes segmentos, como clientes que compram apenas eletrônicos de alta qualidade ou aqueles que apenas compram durante as promoções. Ao ter os segmentos estabelecidos, o varejista pode, então, enviar materiais de marketing direcionados a cada segmento específico, com recomendações personalizadas de produtos ou alertas de acesso antecipado às promoções.\u003C/p\u003E\n"},{"title":"Qual a diferença entre “data analytics” e “data analysis”?","richText":"\u003Cp\u003E“Data analytics” é uma disciplina ampla e abrangente, que inclui a análise de dados (“data analysis”) como uma parte importante do processo. “Data analysis” tem como objetivo entender o passado e o que aconteceu até o momento, descobrir insights práticos e orientar o processo decisório baseado em dados. “Data analytics” usa dados para prever comportamentos futuros, recomendar ações, sendo uma disciplina voltada para o futuro. Enquanto a “data analysis” fornece insights descritivos de dados históricos (já passados), a “data analytics” tem como base criar estratégias voltadas para o futuro, capazes de orientar a ação.\u003C/p\u003E\n"}],":type":"snowflake-site/components/simple-snowflake-accordion","appliedCssClassNames":"snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","simple_snowflake_acc"]},"container_copy_copy__480869401":{"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"customer","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-5aaf82d2f0","additionalClasses":"headline-decoration","type":"heading2","lines":["Clientes Snowflake que usam análises de 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clientes.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical",":type":"snowflake-site/components/card-v2"}},":itemsOrder":["card_v2"]},"flexible_column_content_container_2":{"id":"container-e1a6a3a29b","layout":"SIMPLE","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"card_v2_copy":{"id":"card-v2-148b59c621","configurationStatus":{"configured":true,"message":""},"title":{"id":"title","type":"heading4","lines":["Luminate potencializa a análise de dados de entretenimento com processamento de dados 300% mais rápido e insights mais aprofundados"],":type":"snowflake-site/components/title-v2"},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/customers/all-customers/case-study/luminate/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Ler o caso"},"image":{"id":"image","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--e6364738-9027-4e8f-9985-febcbb81ac1e/luminate-customer-card%25402x.jpg?preferwebp=true&quality=85","alt":"penske logo","lazyEnabled":true,"height":"720","width":"1680",":type":"snowflake-site/components/image"},"type":"content-card","text":{"id":"text","text":"\u003Cp\u003ECom o Snowflake como base, a Luminate (que alimenta as famosas listas de sucessos da Billboard e tem a reputação de ser o parceiro de dados mais confiável da indústria do entretenimento) unificou seus dados para um desenvolvimento de produtos mais inovador e um processamento de dados com tom quase perfeito.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical",":type":"snowflake-site/components/card-v2"}},":itemsOrder":["card_v2_copy"]},":type":"snowflake-site/components/flexible-column-container","isBlogPage":false,"isActiveTOC":false}},":itemsOrder":["title_v2","flexible_column_cont"]},"container_copy_copy__373061683":{"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"resources","layout":"RESPONSIVE_GRID","columnCount":12,"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container",":items":{"title_v2":{"id":"title-v2-2e923193e3","type":"heading2","lines":["Recursos para análise de 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