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Q609404 Redes de Computadores
LDAP é um protocolo muito utilizado para:
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Q609403 Redes de Computadores
Considerando o modelo de referência OSI, podemos afirmar que um roteador, ao determinar e encaminhar pacotes para diferentes redes, está atuando na camada:
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Q609402 Redes de Computadores
Uma conexão Ethernet virtual (EVC - Ethernet Virtual Connection) é um dos conceitos mais importantes em uma nova tecnologia de redes. Uma EVC pode ser considerada como uma instância da associação de duas ou mais UNIs, com o objetivo de transportar um fluxo de dados entre dois ou mais clientes, por meio dessa nova tecnologia. Os EVCs ajudam a visualizar o conceito de conexões e podem ser comparados ao conceito dos PVCs, no ATM. As características aqui citadas referem-se a qual tecnologia?
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Q609401 Redes de Computadores
Sobre os protocolos de roteamento dinâmicos RIP e OSPF, podemos afirmar que:
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Q609400 Redes de Computadores
Um protocolo que é resultado da combinação das funcionalidades de multiplexação estatística e compartilhamento de portas do X.25, com as características de alta velocidade e baixo atraso (delay) dos circuitos TDM; e que utiliza circuitos digitais (PVC e SVC) é o:
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Q609399 Redes de Computadores
Uma tecnologia de comunicação de dados de alta velocidade usada para interligar redes locais, metropolitanas e de longa distância para aplicações de dados, voz, áudio e vídeo, cuja célula contém 48 bytes destinados à informação útil e 5 bytes para cabeçalho é o(a):
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Q609398 Redes de Computadores
No ambiente de protocolos de redes, a seqüência de portas de acesso

25, 110, 23, 21

é associada aos respectivos serviços ou protocolos:

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Q609397 Redes de Computadores
Sobre tipos de recursos do DNS, faça a respectiva associação dos nomes dos recursos ao seu significado ou uso.

I. Mapeamento de um nome para IPv4.

II. Mapeamento de um nome para IPv6.

III. Servidor de e-mail.

IV. Redirecionamento de um nome para outro nome.

V. Associação de certificado TLS.

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Q609396 Redes de Computadores
São resoluções de DNS:
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Q609395 Governança de TI
Observe a seguinte lista.

I. Incidentes.

II. Projetos.

III. Entrega.

IV. SLA.

V. Mudanças.

São gerências no ITIL: 

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Q609390 Inglês

Everyone keeps data. Big organizations spend millions to look after their payroll, customer and transaction data. The penalties for getting it wrong are severe: businesses may collapse, shareholders and customers lose money, and for many organizations (airlines, health boards, energy companies), it is not exaggerating to say that even personal safety may be put at risk. And then there are the lawsuits. The problems in successfully designing, installing, and maintaining such large databases are the subject of numerous books on data management and software engineering. However, many small databases are used within large organizations and also for small businesses, clubs, and private concerns. When these go wrong, it doesn't make the front page of the papers; but the costs, often hidden, can be just as serious.

 Where do we find these smaller electronic databases? Sports clubs will have membership information and match results; small businesses might maintain their own customer data. Within large organizations, there will also be a number of small projects to maintain data information that isn't easily or conveniently managed by the large system-wide databases. Researchers may keep their own experiment and survey results; groups will want to manage their own rosters or keep track of equipment; departments may keep their own detailed accounts and submit just a summary to the organization's financial software.

Most of these small databases are set up by end users. These are people whose main job is something other than that of a Computer professional. They will typically be scientists, administrators, technicians, accountants, or teachers, and many will have only modest skills when it comes to spreadsheet or database software. 

The resulting databases often do not live up to expectations. Time and energy is expended to set up a few tables in a database product such as Microsoft Access, or in setting up a spreadsheet in a product such as Excel. Even more time is spent collecting and keying in data. But invariably (often within a short time frame) there is a problem producing what seems to be a quite simple report or query. Often this is because the way the tables have been set up makes the required result very awkward, if not impossible, to achieve. 

A database that does not fulfill expectations becomes a costly exercise in more ways than one. We clearly have the cost of the time and effort expended on setting up an unsatisfactory application. However, a much more serious problem is the unability to make the best use of valuable data. This is especially so for research data. Scientific and social researchers may spend considerable money and many years designing experiments, hiring assistants and collecting and analyzing data, but often very little thought goes into storing it in an appropriately designed database. Unfortunately, some quite simple mistakes in design can mean that much of the potential information is lost. The immediate objective may be satisfied, but unforeseen uses of the data may be seriously compromised. Next year's grant opportunities are lost.

The word awkward, in the fourth paragraph:
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Q609389 Inglês

Everyone keeps data. Big organizations spend millions to look after their payroll, customer and transaction data. The penalties for getting it wrong are severe: businesses may collapse, shareholders and customers lose money, and for many organizations (airlines, health boards, energy companies), it is not exaggerating to say that even personal safety may be put at risk. And then there are the lawsuits. The problems in successfully designing, installing, and maintaining such large databases are the subject of numerous books on data management and software engineering. However, many small databases are used within large organizations and also for small businesses, clubs, and private concerns. When these go wrong, it doesn't make the front page of the papers; but the costs, often hidden, can be just as serious.

 Where do we find these smaller electronic databases? Sports clubs will have membership information and match results; small businesses might maintain their own customer data. Within large organizations, there will also be a number of small projects to maintain data information that isn't easily or conveniently managed by the large system-wide databases. Researchers may keep their own experiment and survey results; groups will want to manage their own rosters or keep track of equipment; departments may keep their own detailed accounts and submit just a summary to the organization's financial software.

Most of these small databases are set up by end users. These are people whose main job is something other than that of a Computer professional. They will typically be scientists, administrators, technicians, accountants, or teachers, and many will have only modest skills when it comes to spreadsheet or database software. 

The resulting databases often do not live up to expectations. Time and energy is expended to set up a few tables in a database product such as Microsoft Access, or in setting up a spreadsheet in a product such as Excel. Even more time is spent collecting and keying in data. But invariably (often within a short time frame) there is a problem producing what seems to be a quite simple report or query. Often this is because the way the tables have been set up makes the required result very awkward, if not impossible, to achieve. 

A database that does not fulfill expectations becomes a costly exercise in more ways than one. We clearly have the cost of the time and effort expended on setting up an unsatisfactory application. However, a much more serious problem is the unability to make the best use of valuable data. This is especially so for research data. Scientific and social researchers may spend considerable money and many years designing experiments, hiring assistants and collecting and analyzing data, but often very little thought goes into storing it in an appropriately designed database. Unfortunately, some quite simple mistakes in design can mean that much of the potential information is lost. The immediate objective may be satisfied, but unforeseen uses of the data may be seriously compromised. Next year's grant opportunities are lost.

In the fourth paragraph, the expression in bold could be translated to Portuguese by:
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Q609388 Inglês

Everyone keeps data. Big organizations spend millions to look after their payroll, customer and transaction data. The penalties for getting it wrong are severe: businesses may collapse, shareholders and customers lose money, and for many organizations (airlines, health boards, energy companies), it is not exaggerating to say that even personal safety may be put at risk. And then there are the lawsuits. The problems in successfully designing, installing, and maintaining such large databases are the subject of numerous books on data management and software engineering. However, many small databases are used within large organizations and also for small businesses, clubs, and private concerns. When these go wrong, it doesn't make the front page of the papers; but the costs, often hidden, can be just as serious.

 Where do we find these smaller electronic databases? Sports clubs will have membership information and match results; small businesses might maintain their own customer data. Within large organizations, there will also be a number of small projects to maintain data information that isn't easily or conveniently managed by the large system-wide databases. Researchers may keep their own experiment and survey results; groups will want to manage their own rosters or keep track of equipment; departments may keep their own detailed accounts and submit just a summary to the organization's financial software.

Most of these small databases are set up by end users. These are people whose main job is something other than that of a Computer professional. They will typically be scientists, administrators, technicians, accountants, or teachers, and many will have only modest skills when it comes to spreadsheet or database software. 

The resulting databases often do not live up to expectations. Time and energy is expended to set up a few tables in a database product such as Microsoft Access, or in setting up a spreadsheet in a product such as Excel. Even more time is spent collecting and keying in data. But invariably (often within a short time frame) there is a problem producing what seems to be a quite simple report or query. Often this is because the way the tables have been set up makes the required result very awkward, if not impossible, to achieve. 

A database that does not fulfill expectations becomes a costly exercise in more ways than one. We clearly have the cost of the time and effort expended on setting up an unsatisfactory application. However, a much more serious problem is the unability to make the best use of valuable data. This is especially so for research data. Scientific and social researchers may spend considerable money and many years designing experiments, hiring assistants and collecting and analyzing data, but often very little thought goes into storing it in an appropriately designed database. Unfortunately, some quite simple mistakes in design can mean that much of the potential information is lost. The immediate objective may be satisfied, but unforeseen uses of the data may be seriously compromised. Next year's grant opportunities are lost.

In the last paragraph, the line in bold, there is a word not correctly written. It is:
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Q609387 Inglês

Everyone keeps data. Big organizations spend millions to look after their payroll, customer and transaction data. The penalties for getting it wrong are severe: businesses may collapse, shareholders and customers lose money, and for many organizations (airlines, health boards, energy companies), it is not exaggerating to say that even personal safety may be put at risk. And then there are the lawsuits. The problems in successfully designing, installing, and maintaining such large databases are the subject of numerous books on data management and software engineering. However, many small databases are used within large organizations and also for small businesses, clubs, and private concerns. When these go wrong, it doesn't make the front page of the papers; but the costs, often hidden, can be just as serious.

 Where do we find these smaller electronic databases? Sports clubs will have membership information and match results; small businesses might maintain their own customer data. Within large organizations, there will also be a number of small projects to maintain data information that isn't easily or conveniently managed by the large system-wide databases. Researchers may keep their own experiment and survey results; groups will want to manage their own rosters or keep track of equipment; departments may keep their own detailed accounts and submit just a summary to the organization's financial software.

Most of these small databases are set up by end users. These are people whose main job is something other than that of a Computer professional. They will typically be scientists, administrators, technicians, accountants, or teachers, and many will have only modest skills when it comes to spreadsheet or database software. 

The resulting databases often do not live up to expectations. Time and energy is expended to set up a few tables in a database product such as Microsoft Access, or in setting up a spreadsheet in a product such as Excel. Even more time is spent collecting and keying in data. But invariably (often within a short time frame) there is a problem producing what seems to be a quite simple report or query. Often this is because the way the tables have been set up makes the required result very awkward, if not impossible, to achieve. 

A database that does not fulfill expectations becomes a costly exercise in more ways than one. We clearly have the cost of the time and effort expended on setting up an unsatisfactory application. However, a much more serious problem is the unability to make the best use of valuable data. This is especially so for research data. Scientific and social researchers may spend considerable money and many years designing experiments, hiring assistants and collecting and analyzing data, but often very little thought goes into storing it in an appropriately designed database. Unfortunately, some quite simple mistakes in design can mean that much of the potential information is lost. The immediate objective may be satisfied, but unforeseen uses of the data may be seriously compromised. Next year's grant opportunities are lost.

According to the text above:
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Ano: 2014 Banca: Quadrix Órgão: SERPRO Prova: Quadrix - 2014 - SERPRO - Técnico - Suporte |
Q604653 Segurança da Informação
Em um Plano de Recuperação de Desastre, o local externo contratado que permite a configuração e pré-instalação do hardware e dos links de comunicação necessários para, se ocorrer um desastre, carregar o software e os backups de dados recentes para restaurar os sistemas de negócio em até 72h, caracteriza uma solução do tipo:
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Ano: 2014 Banca: Quadrix Órgão: SERPRO Prova: Quadrix - 2014 - SERPRO - Técnico - Suporte |
Q604652 Programação
No TOMCAT o Container Web e um Servlet que realiza compilação de JSP são denominados, respectivamente:
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Ano: 2014 Banca: Quadrix Órgão: SERPRO Prova: Quadrix - 2014 - SERPRO - Técnico - Suporte |
Q604651 Programação
Para definir constantes em PHP utiliza-se a função:
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Ano: 2014 Banca: Quadrix Órgão: SERPRO Prova: Quadrix - 2014 - SERPRO - Técnico - Suporte |
Q604650 Sistemas Operacionais
Trata-se de uma vantagem no uso de bancos de dados baseados em nuvem:
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Ano: 2014 Banca: Quadrix Órgão: SERPRO Prova: Quadrix - 2014 - SERPRO - Técnico - Suporte |
Q604649 Banco de Dados
O processo de analisar grandes bancos de dados de forma semiautomática para encontrar padrões úteis, denominado data mining, usa um conjunto de regras que representa o conhecimento descoberto. Dentre as regras de associação inclui-se ou incluem-se:
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Ano: 2014 Banca: Quadrix Órgão: SERPRO Prova: Quadrix - 2014 - SERPRO - Técnico - Suporte |
Q604648 Redes de Computadores
Os discos da matriz são divididos em 2 grupos. Na escrita, os dados são gravados igualmente nos 2 grupos. Na leitura, os dados podem ser lidos de qualquer um dos grupos. Normalmente, ela é feita alternando-se os discos, processo conhecido por round robin, mas pode haver um disco preferencial para leitura, no caso de haver um disco mais rápido que outro. Não há geração de paridade, mas sim uma redundância completa dos dados. Esse método tem se tornado popular pela sua simplicidade e praticidade em caso de falha de um dos discos. Porém, possui as desvantagens de utilizar apenas metade da capacidade total de discos, além de não trazer nenhum aumento de performance:
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Respostas
581: D
582: C
583: D
584: B
585: B
586: C
587: E
588: A
589: A
590: D
591: B
592: D
593: A
594: C
595: E
596: C
597: B
598: D
599: A
600: D