Questões de Inglês - Compreensão de textos - Analista de Tecnologia da Informação - Desenvolvimento de Sistemas
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Questão: 1 de 13
5446ae8693f0d191f0000078
Banca: VUNESP
Órgão: Instituto de Tecnologia da Informação e Comunicação do Estado do Espírito Santo
Cargo(s): Analista de Tecnologia da Informação - Desenvolvimento de Sistemas
Ano: 2014
Matéria/Assunto: Inglês > Compreensão de textos
da existência de um dado confiável na entrada e do tempo necessário para produzir um dado estável na saída.
da resposta a uma entrada e do tempo gasto para gerar a resposta.
da necessidade de existir um dado na entrada do sistema e da possibilidade de se produzir um dado na sua saída.
das diferentes entradas possíveis no sistema e dos diferentes tempos para a produção das respectivas respostas a essas entradas.
do valor da entrada e do tipo de resposta gerada.
Questão: 2 de 13
620a3a49a79e07198270b161
Banca: Inst. AOCP
Órgão: FUNPRESP
Cargo(s): Analista de Tecnologia da Informação - Desenvolvimento de Sistemas
Ano: 2021
Matéria/Assunto: Inglês > Compreensão de textos
By Eric Knorr - Editor in Chief, CIO | APR 12, 2021 3:00 AM PDT
Some things don't change, even during a pandemic. Consistent with previous years, in CIO’s 2021 State of the CIO survey, a plurality of the 1,062 IT leaders surveyed chose “data/business analytics” as the No.1 tech initiative expected to drive IT investment.
Unfortunately, analytics initiatives seldom do nearly as well when it comes to stakeholder satisfaction.
Last year, CIO contributor Mary K. Pratt offered an excellent analysis of why data analytics initiatives still fail, including poor-quality or siloed data, vague rather than targeted business objectives, and clunky one-size-fits-all feature sets. But a number of fresh approaches and technologies are making these pratfalls less likely.
(...)
New technology invariably incurs new risks. No advancement has had more momentous impact on analytics than machine learning – from automating data prep to detecting meaningful patterns in data – but it also adds an unforeseen hazard. As CSO Senior Writer Lucian Constantin explains in "How data poisoning attacks corrupt machine learning models," deliberately skewed data injected by malicious hackers can tilt models toward some nefarious goal. The result could be, say, manipulated product recommendations, or even the ability for hackers to infer confidential underlying data.
(...)
In the end, the secret to successful analytics is not in choosing and implementing the perfect technology, but in cultivating a broad understanding that pervasive analytics yields better decisions and superior outcomes. Usually, you can iron out technology kinks or requirements misunderstandings. But if you can't change the mindset, few will use the beautiful analytics machine you just built.
Disponível em: https://www.cio.com/article/3614692/5-perspectiveson-modern-data-analytics.html. Acesso em: 15 out. 2021.
Questão: 3 de 13
620a3a49a79e07198270b162
Banca: Inst. AOCP
Órgão: FUNPRESP
Cargo(s): Analista de Tecnologia da Informação - Desenvolvimento de Sistemas
Ano: 2021
Matéria/Assunto: Inglês > Compreensão de textos
By Eric Knorr - Editor in Chief, CIO | APR 12, 2021 3:00 AM PDT
Some things don't change, even during a pandemic. Consistent with previous years, in CIO’s 2021 State of the CIO survey, a plurality of the 1,062 IT leaders surveyed chose “data/business analytics” as the No.1 tech initiative expected to drive IT investment.
Unfortunately, analytics initiatives seldom do nearly as well when it comes to stakeholder satisfaction.
Last year, CIO contributor Mary K. Pratt offered an excellent analysis of why data analytics initiatives still fail, including poor-quality or siloed data, vague rather than targeted business objectives, and clunky one-size-fits-all feature sets. But a number of fresh approaches and technologies are making these pratfalls less likely.
(...)
New technology invariably incurs new risks. No advancement has had more momentous impact on analytics than machine learning – from automating data prep to detecting meaningful patterns in data – but it also adds an unforeseen hazard. As CSO Senior Writer Lucian Constantin explains in "How data poisoning attacks corrupt machine learning models," deliberately skewed data injected by malicious hackers can tilt models toward some nefarious goal. The result could be, say, manipulated product recommendations, or even the ability for hackers to infer confidential underlying data.
(...)
In the end, the secret to successful analytics is not in choosing and implementing the perfect technology, but in cultivating a broad understanding that pervasive analytics yields better decisions and superior outcomes. Usually, you can iron out technology kinks or requirements misunderstandings. But if you can't change the mindset, few will use the beautiful analytics machine you just built.
Disponível em: https://www.cio.com/article/3614692/5-perspectiveson-modern-data-analytics.html. Acesso em: 15 out. 2021.
Questão: 4 de 13
640b52d5cfbaff3b684e82cb
Banca: Inst. AOCP
Órgão: FUNPRESP/JUD
Cargo(s): Analista de Tecnologia da Informação - Desenvolvimento de Sistemas
Ano: 2021
Matéria/Assunto: Inglês > Compreensão de textos
Perspectives on modern data analytics
Questão: 5 de 13
640b52d5cfbaff3b684e82cc
Banca: Inst. AOCP
Órgão: FUNPRESP/JUD
Cargo(s): Analista de Tecnologia da Informação - Desenvolvimento de Sistemas
Ano: 2021
Matéria/Assunto: Inglês > Compreensão de textos
Perspectives on modern data analytics