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System Development Methodology

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Different types of system development methodologies are used in designing information system. Depending upon the actual requirement of the system, different approaches for data processing are adopted. However, some system groups recommend a centralized data processing system while others may go in for a distributed data processing system. In a centralized data processing, one or more centralized computers are used for processing and the retrieval of information is done from them. The distributed processing system involves a number of computers located remotely in the branches/ departments of the organization. The client/ server technology is also gaining popularity these days.

After going through this lesson you would be able to differentiate between the advantages and disadvantages of centralized/ distributed data processing system distinguish between various approaches to the information system explain networking environment explain the meaning of client/ server technology

Data processing system

Data processing techniques are very much dependent on the kind of applications and the working environment. With the progress in technology the concept of integrated data processing has also come into being. In integrated data processing the output data of one application can be used as the input of another application. Depending upon the application area, working environment and the needs of the management, there are basically two approaches to data processing:

  1. Centralized data processing
  2. Decentralized data processing

Centralized data processing System

With the increasing use of computer based data processing, there has been a growing tendency in the minds of management to centralize the data processing activities. Many times the data processing is also done by hiring the services of the outside agencies and with the passage of time and experience in-house set is developed for data-processing.


Following are the advantages of centralized data processing system:

  • The emergence of data takes place only at one place.
  • The loss of data is minimized.
  • The methods and machines can be standardized.
  • Services of more competent and technical personnel can be taken.
  • It is also very cost-effective particularly in the case of large operations.
  • Duplication of work can be avoided.


The disadvantages of the centralized data processing are:

  • Lack of cooperation from managers, who do not like to be under control of centralized Data Processing department.
  • Resistance from managers for mechanization of the data processing activities relating to their various functions.
  • It is difficult to provide equitable services to various departments.
  • The data security is also questioned.

Decentralized Data Processing System

In the decentralized data processing system, there is really a divisional breakdown of computing services. Each division, unit or department handles its own computer needs and does not like to interact with any other division, unit or department. It is well suited to a decentralized management scheme in which organizational autonomy is important. For example, research divisions of a large organization may adopt the decentralized data processing approach to provide data security of their work.


Arguments in support of decentralized data processing include the following: * Familiarity with local problems.

  • Rapid response to local processing needs.
  • Profit-and-loss responsibility can be easily fixed.


The drawbacks of the decentralized data processing system are:

  • There is duplication of activities and redundancy in maintenance of files.
  • It is difficult to maintain uniformity in the procedures throughout the organization.
  • The overall cost of the data processing for the organization is more.
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