There are numerous ways to process electronic data. Thesemethods depend on the data source and the actions the processing unit takes to
produce an outcome in the appropriate format. In a nutshell, processing
electronic large data cannot be done using a "one-size-fits-all"
paradigm.
The main categories into which electronic data can bedivided include the following:
Online processing: In this form, as soon as big data is madeavailable to the system, it is immediately fed into the CPU. The best
illustration of online data processing is barcode scanning.
Big data is gathered and processed in batches during thissort of data processing. The majority of systems that access a large amount of
data, such payroll systems, etc., use this technique.
Real-time processing: This method is used for processingsmall amounts of data. With this approach, as soon as the input data is given,
the result is generated instantly. The ideal example of real-time electronicdata processing is cash withdrawal from an ATM.
Multiprocessing : Data is typically split into two framesand processed using two or more CPUs connected to a single PC in parallel,
which is why this process type is also known as parallel processing. This type of electronic data processing is used in weather forecasting systemsbecause it is necessary to process enormous amounts of data concurrently in
order to deliver reliable, accurate results.
Time-sharing: Using this strategy, multiple people canaccess large amounts of data on numerous computer resources at the same time
and during varied time intervals. This facilitates data processing!
