Centralized Data Processing vs Distributed Data Processing PDF

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Summary

This coursework shows the advantages and disadvantages of Centralized Data Processing and Distributed Data Processing. Accounting Information Systems...

Description

Centralized Data Processing

Centralized data processing occurs when data is processed by a computer system that is located in a central location. For centralized processing to achieve high speed and quick access, a powerful computer is required. All of the data is saved in a centralized data storage system. Protection level decisions and authorized access are the responsibility of the system administrator.

Advantages of Centralized Data Processing 1. Centralized processing helps in reducing the cost because it will not emphasize on more hardware and machines. 2. Centralized processing provides a better data security. 3. Processing is consistent in centralized processing systems. 4. The data and the program on each information system are independent to other information systems. 5. All approvals came from the main

Disadvantages of Centralized Data Processing 1. Large data storage is required at the central information system. 2. It will reduce the local accountability.

3. High traffic can cause input/output bottlenecks. 4. Ability to responds to the information request into a timely manner gets reduced. 5. Needs a high cost in transmitting transactions.

Distributed Data Processing

Users complete their transactions on a local level. Each user group has the IT staff, facilities, hardware, software, and data that they require to run their businesses. Implies self-sufficiency and a reluctance to exchange data and knowledge.

Advantages of DDP. 1. Cost reductions. The main argument for the centralized strategy in the past was to achieve economies of scale. Data processing economics encouraged large, expensive, powerful computers. Because of the vast range of needs that such centralized systems had to meet, computers that were highly generic and used complicated operating systems were required. 2. Powerful yet inexpensive small scale, which can cost-effectively perform specialized functions, have changed the economics of data processing dramatically. Furthermore, the unit cost of data storage, which was formerly the primary basis for centralizing data, is no longer the primary factor. Moreover, switching to DDP can save money in two ways: (1) data can be entered and changed at the IPU, removing the need for centralized data

conversion and control; and (2) application complexity can be decreased, lowering development and maintenance expenses. 3. Improved cost control responsibility. Managers are accountable for the financial success of their businesses. This necessitates them being adequately empowered with the authority to make resource decisions that have an impact on their overall success. Shouldn't management be granted authority over these resources if informationprocessing capability is crucial to the success of a commercial operation? This argument is in opposition to the previous one, which advocates for the concentration of organization-wide resources. The benefits of enhanced management attitudes, according to DDP supporters, offset the higher expenses of delivering these resources.

4. Improved user satisfaction. Improved customer pleasure is perhaps the most frequently mentioned benefit of DDP. This stems from three areas of need that, in the centralized model, are all too often unmet: Users want to be more actively involved in developing and implementing their own systems for three reasons: (1) they want control over the resources that influence their profitability; (2) they want systems professionals (analysts, programmers, and computer operators) who are responsive to their specific situation; and (3) they want to become more actively involved in developing and implementing their own systems, as previously stated. DDP proponents say that offering more personalized support—which can only be done in a distributed environment—improves user morale and productivity. 5. Backup. The ability to back up computing infrastructure to safeguard against probable calamities such as fires, floods, sabotage, and earthquakes is the ultimate reason in favor of DDP. One option is to include additional capacity in each IPU. If a single site is destroyed by a disaster, the other IPUs can complete the transactions. This necessitates close cooperation among decision-makers to guarantee that incompatible hardware and software are not installed at their locations.

Disadvantages of DDP

1. Mismanagement of organization-wide resources. Some claim that when an organization's resources transcend a certain threshold, such as 5% of the total operations budget, they should be centralized controlled and monitored. Many organizations spend a large amount of money on information processing services (such as computer operations, programming, data conversion, and database maintenance). Those who oppose DDP say that delegating responsibility for these resources will ultimately lead to mismanagement and inefficient use. 2. Hardware and software incompatibility. Distributing the responsibility for hardware and software purchases to user management can result in uncoordinated and poorly conceived decisions. Working independently, decision makers may settle on dissimilar and incompatible operating systems, technology platforms, spreadsheet programs, word processors, and database packages. Such hardware and software incompatibilities can degrade and disrupt communications between organizational units. 3. Redundant tasks. Because autonomous systems development activities are spread around the company, each user area may end up spinning the wheel. For example, rather of sharing application programs produced by one user that might be utilized with little or no modification by others, they will be redesigned from the ground up. Similarly, data that is shared by numerous users may be reproduced for each IPU, resulting in substantial data redundancy. 4. Consolidating incompatible activities. The distribution of IT functions to specific user regions results in the formation of a large number of very small units, which may not allow for the separation of incompatible tasks that is required. Within a single IPU, for example, the same individual may program applications, maintain programs, enter transaction data into the computer, and operate the computer equipment. This circumstance is a serious breach of internal control. 5. Hiring qualified professionals. End-user managers may be unable to assess the technical qualifications and relevant experience of people applying for a position as a computer professional due to a lack of expertise. Furthermore, if the organizational unit into which a new employee is being hired is tiny, personal growth, continuing education, and promotion opportunities may be limited. As a result of these factors, IPU managers

sometimes have trouble hiring highly qualified staff, increasing the likelihood of programming errors and system breakdowns. 6. Lack of standards. Standards for designing and documenting systems, choosing programming languages, obtaining hardware and software, and evaluating performance may be unevenly applied or nonexistent in the DDP context due to the dispersion of responsibility. Opponents of DDP claim that only if such rules are consistently enforced can the risks involved with the design and operation of a data processing system be tolerated. This necessitates the imposition of norms from a central location....