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Centralized data processing is processing performed in one computer or in a cluster of coupled computers in a single location. Access to the computer is via "dumb terminals," which send only input and receive output or "smart terminals," which add screen formatting. This means that all data processing is performed in the central computer. On the other hand Distributed data processing is processing performed by different computer at different locations.
Examples of Centralized data processing:
A situation like in a ticket allocating system for a plane, all the requests are handled from a central location.
A banking system for ATM where all data is handled by a single server in given location.
Example of Distributed processing
A company that produces goods with different offices can choose to have each department have computers to process their own data and submit information.I will upload the answer to the last part soon
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Centralized processing and cloud computing:
Cloud computing relies on third party data centers to process data while centralized data processing makes use of a central server computer. Centralized data processing may face challenges in case of a break down as opposed to cloud computing where one different servers can be used to do processing. In cloud computing too, processing may take longer when the tasks to be handled are too many while with cloud computing the available processor is allocated the task.
Distributed Data processing:
With distributed data processing, data is processed at different machine located at different physical locations. This means that the processor may be idle when there is no data to be processed. This translates in to under-use of the given resource. With cloud computing, it is not easy to have a processor idle since it is a shared resource thus utilizing its power.
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