mc0076 fall 2012 full assignment

Master of Computer Applications Sikkim Manipal UniversityDirectorate of Distance Education

Assignment

Name : Gaurav Singh Jantwal

Registration No. :

Learning Center :

Learning Center Code

:

Course : MCA

Subject : MC0076 – Management and Information Systems

Semester : IV Semester

Module No. :

Date of submission :

Marks awarded :

Directorate of Distance EducationSikkim Manipal UniversityII Floor, Syndicate House

Manipal – 576104

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_Signature of Coordinator Signature of Center Signature of Evaluator

Gaurav Singh Jantwal 511230075


Comments by the Subject Evaluator:

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Suggestions for improvement:

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1. What do you understand by Information processes data?

Answer 1: Information is a complex concept that has a variety of meanings depending on its context and the perspective in which it is studied. It could be described in three ways –

1. As processed data,2. As the opposite of uncertainty, and3. As a meaningful signal-to illustrate the richness of the concept of information.

Information as Processed DataData are generally considered to be raw facts that have undefined uses and application; information is considered to be processed data that influences choices, that is, data that have somehow been formatted, filtered, and summarized; and knowledge is considered to be an understanding derived from information distinctions among data, information, and knowledge may be derived from scientific terminology. The researcher collects data to test hypotheses; thus, data refer to unprocessed and unanalyzed numbers. When the data are analyzed, scientists talk about the information contained in the data and the knowledge acquired from their analyses. The confusion often extends to the information systems context, and the three terms maybe used interchangeably.

Information as the Opposite of UncertaintyA different perspective on information derives from economic theory and defines information as the negative mea-sure of uncertainty; that is, the less information is available, the more uncertainty exists, and conversely, the more information is available, the less uncertainty exists? In microeconomic theory the equilibrium of supply and demand depends on a market known as a perfect market, where all buyers and sellers have complete knowledge about one another and where uncertainty does not exist. Information makes a market perfect by eliminating uncertainties about supply and demand. In macroeconomic theory, firms behave according to how they read the economic climate. Economic signals that measure and predict the direction of the economy provide information about the economic climate. The firm reduces its uncertainty by decoding these signals. Taking an example of Federal Express in USA, each incoming aircraft has a scheduled arrival time. However, its actual arrival depends on unforeseen conditions. Data about when an aircraft departed from its destination is information in the economic sense because it reduces uncertainty about the aircraft’s arrival time, thereby increasing Federal Express’s ability to handle arriving packages. Managers also define information in terms of its reducing uncertainty. Because managers must project the outcomes of alternatives in making decisions, the reduction of uncertainty about the outcomes of various alternatives improves the effectiveness of the decision- making process and the quality of the decision.

Information as a Meaningful SignalInformation theory, a branch of statistics concerned with measuring the efficiency of communication between people and/or machines, defines information as the inputs and outputs of communication. Electronic, auditory, visual, or other signals that a sender and receiver interpret similarly convey information. For example, in the recruitment scenario about, the resumes and applications for the open positions are information because they are signals sent by the applicants, and interpreted similarly by both. The Managers in their roles as communicators both generate and receive information. They receive reports that organize signals or data in a way that conveys their meaning. Reports of sales trends become information; so do reports about hazardous waste sites. Managers derive meaning from the information they see and hear as part of communication and use it to make decisions. This definition of information requires a manager to interpret a given signal as it was intended. For example, a manager’s incorrect interpretation of body language in a negotiation would not be considered to be information from this perspective, although we know that managers use both correct and incorrect perceptions as information in decision making and other managerial functions. Again, this view of information suggests the complexity of the concept and the value of a multifaceted definition.



2. How do you retrieve information from manual system?

Answer 2 : Information retrieval (IR) is the area of study concerned with searching for documents, for information within documents, and for metadata about documents, as well as that of searching structured storage, relational databases, and the World Wide Web. There is over lap in the usage of the terms data retrieval, document retrieval, information retrieval, and text retrieval, but each also has its own body of literature, theory, praxis, and technologies. IR is interdisciplinary, based on computer science, mathematics, library science, information science, information architecture, cognitive psychology, linguistics, statistics and law.

Key Drawbacks in Manual Paper Based Systems: No transparency. Limited accountability. Can’t retrieve information quickly. Chance of loss. Can’t track or monitoring status of file processing. Scope for tampering contents. Not able to answer customer questions. Status of file is not known to the applicant. Entire organization is dependent on the file custodian for answers.

Manual processes can be unreliable, slow and error prone. Errors reduce confidence in the organization. Is Restricted to onsite working hours and geography. Manual data entry, searching for lost files, and manual rework waste time and valuable resources. Papers can be lost at any point along the process, exposing potentially sensitive data. Physical papers can be hard to track and take up physical space for storage.

Retrieving desired data from manual systems can be time consuming and expensive executives spend approximately six weeks a year on average looking for misplaced material. Secretaries may spend as much as 30 percent of their time looking for paper documents and approximately 20 percent of that time searching for misfiled items. Because paper files require large amounts of space, managers may store the data on a different floor or even in a different building. The labor costs of retrieving even small amounts of information exceed those for retrieving information electronically unless the organization can create small and compact storage for its paper records.

Electronic systems provide rapid and inexpensive access to information stored electronically in an organized fashion. The costs incurred are only those of using the computer equipment for a fraction of a second, particularly when retrieval is part of ongoing processing. If an individual requests the retrieval, it may require additional processing to translate the retrieval request from a form understood by the person to a form understood by the computer. Then the information is stored in a different place from where it is requested, the request must be transmitted electronically to where the data are stored, and the retrieved data must be transmitted back. Communication costs are relatively low for small amounts of information, but the communication equipment and infrastructure can be expensive unless amortized over a sufficiently large volume of data communication. Companies that have small communication needs can pay to use the infrastructure of third parties, such as telephone companies.


http://en.wikipedia.org/wiki/Law

http://en.wikipedia.org/wiki/Statistics

http://en.wikipedia.org/wiki/Linguistics

http://en.wikipedia.org/wiki/Cognitive_psychology

http://en.wikipedia.org/wiki/Cognitive_psychology

http://en.wikipedia.org/wiki/Information_architecture

http://en.wikipedia.org/wiki/Library_science

http://en.wikipedia.org/wiki/Library_science

http://en.wikipedia.org/wiki/Mathematics

http://en.wikipedia.org/wiki/Computer_science

http://en.wikipedia.org/wiki/Interdisciplinary

http://en.wikipedia.org/wiki/Praxis_(process)

http://en.wikipedia.org/wiki/Text_retrieval

http://en.wikipedia.org/wiki/Document_retrieval

http://en.wikipedia.org/wiki/Computer_data

http://en.wikipedia.org/wiki/World_Wide_Web

http://en.wikipedia.org/wiki/Relational_database

http://en.wikipedia.org/wiki/Structured_storage

http://en.wikipedia.org/wiki/Metadata_(computing)


3. What are the challenges of information management?

Answer 3:

Challenges of Information Management

In identifying their information management requirements, individuals face four major challenges in addition to securing the most appropriate information.

First, they must deal with large quantities of information that may create overload.

Second, they may face insufficient or conflicting information.

Third, they must find ways to enhance their personal productivity.

Fourth, they must acquire and maintain the technical skills needed for effective personal information management.

Dealing with Quantities of Information

The gap between the amount of information that an organization can collect and the ability of its employees to make sense of that information has been widening rather than narrowing. The early fear that computers would so improve a person’s ability to process and manage information that a jobholder would need only one-third to one-half the time to do his or her job has been dispelled The reverse has occurred. Often employees face an information glut, an overload of information. As individuals move higher in the organizational hierarchy and assume more managerial responsibility, information overload become an even more significant challenge. To avoid such overload individuals must carefully asses their information needs and then find effective ways of managing the required and available information. They must also find ways to manage data better.

Facing Insufficient or Conflicting Information

Although computers can make large quantities of information available to individuals, such information may not address their needs. Ramesh, ASM of Airtel, may wish to do some library research about competitors’ products. In spite of the large amount of information in the library’s electronic catalog, she may not be able to secure the precise information she needs. Because computers process input from diverse sources, users may also obtain conflicting information if one source updates information more frequently than another does.

Enhancing Personal Productivity

Employees in any organization increasingly use information technology to improve their personal productivity. To ensure high productivity, employees must know how to use computers to facilitate, not hinder, their performance. They must know how to access the information they require and recognize when manual data collection and processing is adequate. Often employees must lobby their employers to add new technology that will help increase personal productivity. The ability to show the cost-effectiveness of additional expenditures for diagnosing and meeting information needs is critical. Employees must also understand and demonstrate when advanced technology is a detriment rather than an asset.

Maintaining Technical Skills

Finally, using information technology effectively requires continuous updating of technical skills. Although many companies provide training to their employees, others do not. Ensuring that employees have the appropriate skills has both financial and time cost implications. As a result, employees may find their mobility and productivity limited by the extent to which they can learn new technical skills independently of their employer.



4. Explain the different components of MIS.

Answer 4:

The components of MIS

The physical components of MIS comprise the computer and communications hardware, software, database, personnel, and procedures. Almost all organizations employ multiple computer systems, ranging from powerful mainframe machines (sometimes including supercomputers) through minicomputers, to widely spread personal computers (also known as microcomputers). The use of multiple computers, usually interconnected into networks by means of telecommunications, is called distributed processing. The driving forces that have changed the information processing landscape from centralized processing, relying on single powerful mainframes, to distributed processing have been the rapidly increasing power and decreasing costs of smaller computers.

Though the packaging of hardware subsystems differs among the three categories of computers (mainframes, minicomputers, and microcomputers), all of them are similarly organized. Thus, a computer system comprises a central processor (though multiprocessors with several central processing units are also used), which controls all other units by executing machine instructions; a hierarchy of memories; and devices for accepting input (for example, a keyboard or a mouse) and producing output (say, a printer or a video display terminal). The memory hierarchy ranges from a fast primary memory from which the central processor can fetch instructions for execution; through secondary memories (such as disks) where on-line databases are maintained; to the ultra high capacity archival memories that are also employed in some cases.

COMPONENT DESCRIPTION

Hardware Multiple computer systems: mainframes, minicomputers, personal computers.

Computer system components are: central processor(s), memory hierarchy, input and output devices.

Communications: local area networks, metropolitan area networks, and wide area networks.

Software Systems software and applications software.

Database Organized collections of data used by applications software.

Personnel Professional cadre of computer specialists; end-users in certain aspects of their work.

Procedures Specifications for the use and operation of computerized information systems collected in user manuals, operator manuals, and similar documents.

Multiple computer systems are organized into networks in most cases. Various network configurations are possible, depending upon an organization’s need. Fast local area networks join machines, most frequently clusters of personal computers, at a particular organizational site such as a building or a campus. The emerging metropolitan area networks serve large urban communities. Wide area networks connect machines at remote sites, both within the company and in its environment. Through networking, personal-computer users gain access to the broad computational capabilities of large machines and to the resources maintained there, such as large databases. This connectivity converts personal computers into powerful workstations.

Computer software falls into two classes: systems software and applications software. Systems software manages the resources of the system and simplifies programming. Operating systems (UNIX, for example) control all the resources of a computer system and enable multiple users to run their programs on a computer system without being aware of the complexities of resource allocation. Even if you are just using a personal computer, a complex series of actions takes place when, for example, you start the machine, check out its hardware, and call up a desired program. All of these actions fall under the control of an operating system, such as DOS or IBMOS/2. Telecommunications monitors manage computer communications; database management systems make it possible to organize vast collections of data so that they are accessible for fast and simple queries and the production of reports. Software translators-compilers or interpreters, make it possible to program an application in a higher-level language, such as COBOL or C. The translator converts program statements into machine instructions ready for execution by the computer’s central processor.

Many categories of applications software are purchased as ready-to-use packages. Applications software directly assists end users in their functions. Examples include general-purpose spreadsheet or word processing programs, as well as the so-called vertical applications serving a specific industry segment (for example, manufacturing resource planning systems or accounting packages for small service businesses). The use of purchased application packages is increasing. However,



the bulk of applications software used in large organizations are developed to meet a specific need. Large application systems consist of a, number of programs integrated by the database.

To be accessible, data items must be organized so that individual records and their components can be identified and, if needed, related to one another. A simple way to organize data is to create files. A file is a collection of records of the same type. For example, the employee file contains employee records, each containing the same fields (for example, employee name and annual pay), albeit with different values. Multiple files may be organized into a database, or an integrated collection of persistent data that serves a number of applications. The individual files of a database are interrelated. Professional MIS personnel include development and maintenance managers, systems analysts, programmers, and operators, often with highly specialized skills. The hallmark of the present stage in organizational computing is the involvement of end users to a significant degree in the development of information systems. Procedures to be followed in using, operating, and maintaining computerized systems are a part of the system documentation.



5. Mention different characteristics of MRS.

Answer 5:

Characteristics of MRS

1) MRS are usually designed by MIS professionals, rather than end users, over an extensive period time, with the use of life-cycle oriented development methodologies (as opposed to first building a simpler prototype system and then refining it in response to user experience). Great care is exercised in developing such systems because MRS is large and complex in terms of the number of system interfaces with various users and databases.

2) MRS is built for situations in which information requirements are reasonably well known and are expected to remain relatively stable. Modification of such systems, like their development, is a rather elaborate process. This limits the informational flexibility of MRS but ensures a stable informational environment.

3) MRS does not directly support the decision-making process as a search for alternative solutions to problems. Naturally, information gained through MRS is used in the manager’s decision-making process. Well-structured decision rules, such as economic order quantities for ordering inventory or accounting formulas for computing various forms of return on equity, are built into the MRS itself.

4) MRS is oriented towards reporting on the past and the present, rather than projecting the future.5) MRS generally has limited analytical capabilities-they are not built around elaborate models, but rather rely on

summarization and extraction from the database according to given criteria. Based on simple processing of the data summaries and extracts, report information is obtained and printed (or, if of limited size, displayed as a screen) in a pre-specified format.

6) MRS generally report on internal company operations rather than spanning the company’s boundaries by reporting external information.



6. Discuss the following with respect to DSS:

Answer 6: a. Components of DSS

The three principal DSS subsystems and their principal capabilities are shown in figure below. Various commercial systems support DSS development and package these DSS capabilities in a variety of ways by distributing them among a series of optional modules.

Data Management Subsystem

The data management subsystem of a DSS relies, in general, on a variety of internal and external databases. Indeed, we have said that the power of DSS derives from their ability to provide easy access to data. This is not to say that a simple, usually spreadsheet-based DSS for the personal use of a manager cannot rely on the manager’s limited personal database. It is simply that maintaining the currency and integrity of a significant database of this kind is usually a daunting task. Proliferation of personal databases also contradicts the principles of information resource management.



Management Subsystem

On the other hand, it is usually undesirable to provide a DSS with direct access to corporate databases. The performance of the transaction processing systems that access these databases, as well as the responsiveness of the DSS, would both be degraded. Usually, therefore, the database component of DSS relies on extracts from the relevant internal and external databases. The user is able to add to these data at will. This is shown in figure 10.2.The extraction procedure itself is generally specified by a specialist rather than an end user. The specialist needs to pay particular attention to data consistency across multiple decision support systems that extract data from the corporate databases. If extracts for the DSS serving the same functional area are made at different times, the extracted databases will differ and “battles of the printout" may result.

The Model Management Subsystem

The power of DSS rests on the user’s ability to apply quantitative, mathematical models to data. Models have different areas of application and come from a variety of sources. Software packages for developing DSS (so-called DSS generators) contain libraries of statistical models. These models include tools for the exploratory analysis of data-tools designed to obtain summarized measures such as mean and median values, variances, scatter plots, and so forth. Other statistical models help analyze series of data and forecast future outcomes by approximating a set of data with a mathematical equation, by extending the trend of a curve by extrapolation techniques, or by providing for seasonal adjustment. The capabilities of the model management component of DSS are summarized in figure.

Other models help establish (or reject) causal relationships between various factors (for example, whether the drop in sales volume is caused by the aging of our target market segment). Market response models show how sales depend on such factors as price and promotion. Simulation models that generate input values randomly from a certain probability



distribution (also called Monte Carlo models-after the city where the famous casino is, of course) are employed for waiting-line problems, such as establishing the number of operators needed for order taking or deciding on staffing levels for a service center.

Model Management Subsystem

Optimization models, developed by management scientists, are available for use in DSS. These models aim to allocate resources to maximize profit or minimize cost or time. A number of such models are based on a linear programming technique. These include models that allocate input resources (labor, materials, and capital) among various products; models that assign activities to personnel or equipment; and models that determine the best shipping schedules from several points of origin to several destinations. Other models optimize inventory levels or determine optimal network configurations. Specialized model libraries are available for financial modeling, risk analysis, or marketing.

A particular advantage of DSS is the decision maker’s ability to use a model to explore the influence of various factors on outcomes (a process known as sensitivity analysis). Two forms of such analysis are the what-if analysis and goal seeking.

When doing what-if analysis, the decision maker creates multiple scenarios by assuming various realistic values for input data, Thus, the decision maker asks "What if these are the values of the inputs?" The model re-computes outputs for each case. Here are some examples of questions that can be directed toward appropriate models:

What will be the cost of goods sold if the cost of raw materials increases by10 percent? What will be the effects on the company bonus program if sales increase by3 percent and direct expenses

increase by 5 percent? When goal seeking, the decision maker works backward from the assumed results to the needed input values.

Thus, the decision maker asks "What will it take to achieve this goal?" Some examples of questions asked in this mode are:

What sales volume will be necessary to ensure a revenue growth of 10 percent next year? How many service center employees will it take to ensure that every order is handled within three minutes? What quarterly revenues will we need from each of our three products to generate the desired profits during

these quarters?

The actual form in which these questions may be asked depends on the options offered by the dialog management subsystem of the DSS, which we shall discuss next.

There is significant research interest in providing a degree of automated model management. The user would be able to present the problem in a system of this kind, and the system would automatically select an appropriate model or construct one from the existing models and "building blocks."

The Dialog Management Subsystem



Along with DSS’s ability to apply models to large volumes of data from a variety of sources, a single advantage of DSS is the user-friendly and flexible interface between the human decision maker and such a system. This stands in contrast to management reporting systems. The notable feature is support of multiple forms of input and output. By combining various input and output capabilities of a DSS, users can engage in the individual dialog styles that best support their decision-making styles. The field of artificial intelligence has made some notable contributions to dialog management, such as the ability to specify what is wanted in a subset of natural language or to activate the system by voice. The window capability enables the user to maintain several activities at the same time, with the results displayed in screen windows (the user employs a mouse to move between the windows). A variety of help and even training-by-example capabilities may be offered. Significant attention has been devoted by researchers to the effectiveness of computer graphics, as opposed to the tabular display of data. Gary Dickson and his colleagues found that, in general, one cannot claim an advantage (however intuitively appealing it may he) for graphics throughout all decision-related activities. They did find, however, that graphs outperform tables when a large amount of information must be presented and a relatively simple impression is desired. This is very often the case-and the main reason why executive information systems, discussed later in this chapter, rely heavily on graphics.

By analyzing the results of research in this area, Ali Montazemi and Shuohong Wang, concluded that line graphics have time-saving effects on decision making for more complex decision tasks only, and are less defective at providing precise information. Color graphics were found to improve decision quality, but they did not reduce the time necessary to arrive at a decision. Graphic representation of quantitative information requires considerable care to prevent distorted perception; Edward Tuft gives a thorough and exciting presentation of the subject.

Summarizing the uses of graphical presentation of business information, Richard Scovill tells us that most business graphs are designed to answer just four questions:

1. Who is the biggest?2. How do circumstances change over time?3. What is typical or exceptional?4. How well does one fact predict another?

In general, it has been established that different decision makers and tasks are best supported by different display formats. This again proves that the advantage of DSS in the area of dialog management lies in providing a variety of dialog styles.



b. Classification of DSS1. On Use level DSS is classified as

a. Passive DSS: A passive DSS is a system that aids the process of decision making, but that cannot bring out explicit (clear) decision suggestions or solutions.

b. Active DSS: An active DSS can bring out explicit decision suggestions or solutions.

c. Cooperative DSS: A cooperative DSS allows the decision maker (or its advisor) to modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation. The system again improves, completes, and refines the suggestions of the decision maker and sends them back to her for validation. The whole process then starts again, until a consolidated solution is generated.

2. On the conceptual level DSS is classified asa. Communication-driven DSS:

A communication-driven DSS supports more than one person working on a shared task e.g. integrated tools like Microsoft's NetMeeting or Groove .

b. Data-driven DSS:A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.

c. Document-driven DSS:A document-driven DSS manages, retrieves and manipulates unstructured information in a variety of electronic formats.

d. Knowledge-driven DSS:A knowledge-driven DSS provides specialized problem solving expertise stored as facts, rules, procedures, or in similar structures.

e. Model-driven DSS:A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by DSS users to aid decision makers in analyzing a situation, but they are not necessarily data intensive.

3. On System level DSS is classified asa. Enterprise-wide DSS:

Enterprise-wide DSS are linked to large data warehouses and serve many managers in a company.b. Desktop DSS:

Desktop, single-user DSS are small systems that reside on an individual manager’s PC.


mc0076 fall 2012 full assignment

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