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Comments about The analysis phase - The Analysis Phase: identification and description of the types of information needed to analyse the system

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- Module: The analysis phase
- Topic: The Analysis Phase: identification and description of the types of information needed to analyse the system

Latest Comments

  • Samuel Kofi Odoi Ghana It is unusual for one user to be the exclusive source of information about the system. Most aspects of the system will have some degree of overlap - it may be that significant detail will come mainly from one source, but there will usually be other users who are also impacted, and information must be collected from them as well. As well as identifying who will be capable of supplying what information in this step, the analyst must also make decisions about the reliability and suitability of the sources. Information collected must be evaluated for bias and relevance and given the appropriate weighting in the overall analysis of the system. For example, while a manager and a data clerk would both have opinions on the usefulness of the financial reports produced by a particular system, the manager's opinion would have more weighting, but conversely, the data clerk's opinion has more significance in areas relating to the ease of data entry. Sometimes, the analyst will identify the need for other information in order to fully analyse the system. In this case, they would need to document where this information can be obtained. An example of this would be the need to conform to government privacy regulations with regard to the release of confidential data on individuals. How can this lodge as confidential document. can a system be design for it confidentiality use?
    2014-10-20 04:10:54

  • Ralph Webster South Africa Having identified the sources of information, the next step the analyst must take is to establish what information can be gained from them. The information which can be gained from the manager will be different from the data entry clerk, which will be different from the customers and so on. The analyst must decide what information should be obtained from each source identified. It is unusual for one user to be the exclusive source of information about the system. Most aspects of the system will have some degree of overlap - it may be that significant detail will come mainly from one source, but there will usually be other users who are also impacted, and information must be collected from them as well. As well as identifying who will be capable of supplying what information in this step, the analyst must also make decisions about the reliability and suitability of the sources. Information collected must be evaluated for bias and relevance and given the appropriate weighting in the overall analysis of the system. For example, while a manager and a data clerk would both have opinions on the usefulness of the financial reports produced by a particular system, the manager's opinion would have more weighting, but conversely, the data clerk's opinion has more significance in areas relating to the ease of data entry. Sometimes, the analyst will identify the need for other information in order to fully analyse the system. In this case, they would need to document where this information can be obtained. An example of this would be the need to conform to government privacy regulations with regard to the release of confidential data on individuals.
    2014-10-19 10:10:32

  • George Fragos Greece Why it is unusual for a user to be the exclusive source of information about the system?
    2014-10-01 09:10:42

  • ANNETTE ROBINSON United States of America I need to do a little more research on this area. Can someone explain it a little more in layman's term?
    2014-09-09 12:09:39

  • Saw Minyau Germany How can we analysis for bias in project system?
    2014-08-16 00:08:49

    • Yai Deng Yai South Sudan After getting information from different sources that are involved in project work.
      2014-08-25 16:08:24
  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:07

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:52

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:40

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:25

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:13

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:59

  • Jones Hanungu Munang'andu Zambia Management support Management reporting systems A large category of information systems comprises those designed to support the management of an organization. Those systems rely on data obtained by transaction processing systems, as well as data acquired outside the organization (such as business intelligence gleaned on the Internet) and data provided by business partners, suppliers, and customers. Information systems support all levels of management, from those in charge of short-term schedules and budgets for small work groups to those concerned with long-term plans and budgets for the entire organization. Management reporting systems provide routine, detailed, and voluminous information reports specific to each manager's areas of responsibility. Generally, these reports focus on past and present performance, rather than projecting future performance. To prevent information overload, reports are automatically sent only under exceptional circumstances or at the specific request of a manager. Decision support systems All information systems support decision making, however indirectly, but decision support systems are expressly designed for this purpose. The two principal varieties of decision support systems are model-driven and data-driven. In a model-driven decision support system, a preprogrammed model is applied to a limited data set, such as a sales database for the present quarter. During a typical session, an analyst or sales manager will conduct a dialog with this decision support system by specifying a number of “what-if” scenarios. For example, in order to establish a selling price for a new product, the sales manager may use a marketing decision support system. Such a system contains a preprogrammed model relating various factors—the price of the product, the cost of goods, and the promotion expense—to the projected sales volume over the first five years on the market. By supplying different product prices to the model, the manager can compare predicted results and select the most profitable selling price. The primary objective of data-driven decision support systems is to analyze large pools of data, accumulated over long periods of time in “data warehouses,” in a process known as data mining. Data mining searches for significant patterns, such as sequences (buying a new house, followed by a new dinner table) and clusters (large families and van sales), with which decisions can be made. Data-driven decision support systems include a variety of statistical models and rely on various artificial intelligence techniques, such as expert systems, neural networks, and intelligent agents. An important category of decision support systems enables a group of decision makers to work together without necessarily being in the same place at the same time. These group decision systems include software tools for brainstorming and reaching consensus. Another category, geographic information systems, can help analyze and display data by using digitized maps. By looking at a geographic distribution of mortgage loans, for example, one can easily establish a pattern of discrimination. Executive information systems Executive information systems make a variety of critical information readily available in a highly summarized and convenient form. Senior managers characteristically employ many informal sources of information, however, so that formal, computerized information systems are of limited assistance. Nevertheless, this assistance is important for the chief executive officer, senior and executive vice presidents, and the board of directors to monitor the performance of the company, assess the business environment, and develop strategic directions for the future. In particular, these executives need to compare their organization's performance with that of its competitors and investigate general economic trends in regions or countries for potential expansion. Often relying on multiple media, executive information systems give their users an opportunity to “drill down” from summary data to increasingly detailed and focused information.
    2014-07-20 19:07:39

  • Daniel Chol Koknyin South Sudan What will happen if the information is bias and not realistic or suitable?
    2014-07-05 20:07:08

    • Yai Deng Yai South Sudan It cannot be used for analysis and more information would be gathered from different sources.
      2014-08-25 16:08:07
    • Philip Pam Nigeria definitely the result will be unreliable
      2014-08-23 21:08:48
  • ToeToe Aung Singapore Would analyst need to document where the information can be obtained?
    2014-06-29 03:06:05

    • Yai Deng Yai South Sudan Yes.
      2014-08-25 16:08:40
    • Kyaw Ko Ko Lwin Singapore Of course, analyst must be documented all functional upon collected information.
      2014-07-08 15:07:08
  • ToeToe Aung Singapore What types of information should be collected by analysts before making the decisions?
    2014-06-28 10:06:29

    • Yai Deng Yai South Sudan relevant and accurate one concern project being done.
      2014-08-25 16:08:27
  • Reza Abbasi Iran What decisions are important for the analyst?
    2014-06-22 15:06:27

    • Yai Deng Yai South Sudan Whether to take action ot not.
      2014-08-25 16:08:19
    • Philip Pam Nigeria All that is relevant.
      2014-08-23 21:08:52
  • Reza Abbasi Iran What decisions are important for the analyst?
    2014-06-20 00:06:42

  • Annette Weizbauer Germany After having identified the sources of information, what do the analyst must take as the next step?
    2014-06-15 16:06:43

    • Yai Deng Yai South Sudan Finding out if the source is reliable.
      2014-08-25 16:08:19
    • Reza Abbasi Iran Having identified the sources of information, the next step the analyst must take is to establish what information can be gained from them. The information which can be gained from the manager will be different from the data entry clerk, which will be different from the customers and so on. The analyst must decide what information should be obtained from each source identified.
      2014-06-20 00:06:35
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