DATA PROCESSING METHODS

Data that is stored is processed in three different ways. Processing data means retrieving data and deriving information from data. Depending upon where it is done and how it is done, there are three methods.

• Centralized data processing
• De-centralized data processing 
• Distributed data processing 

Centralized data processing :

In this method the entire data is stored in one place and processed there itself. Mainframe is best example for this kind of processing. The entire data is stored and processed on mainframe. All programs, invoked from clients (dumb terminals), are executed on the mainframe and data is also stored in mainframe.
As you can see in figure 6, all terminals are attached to mainframe. Terminals do not have any processing ability. They take input from users and send output to users. 

Decentralized data processing  : 

 In this data is processed at various places. A typical example is each department containing its own system for its own data processing needs. See figure 7, for an example of decentralized data processing. Each department stores data related to itself and runs all programs that process its data. But the biggest drawback of this type of data processing is that data is to be duplicated. As common data is to be stored in each machine, it is called as redundancy. This redundancy will cause data inconsistency. That means the data stored by two departments will not agree with each other.

Data in this mode is duplicated, as there is no means to store common data in one place and access from all machines.