Introduction to Data Processing
Data processing means to process the data i.e. to convert its format. As we all know data is the very useful and when it is well presented and it becomes informative + useful. Data processing system is also referred as information system. It is also right to say that data processing becomes the process of converting information into data and also vice-versa.
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In simple words, data processing can be expressed as :
- Process of conversion of data in the computer understandable format.
- The sorting or processing of data by a computer.
Types of data processing :
Data processing is broadly divides into two categories : Business, Scientific, and Real time Data Processing. These are explained as following below.
- Business Data Processing :
The process of data in the accounting or business management referred as business or administrative data processing. In this type of data processing, data is usually in the numeric form. It refers to the all the computing functions that occur in an enterprise. The computer that is oriented towards business data processing will demand for high speed input and output so that conversion of stored data into report format can occur easily.
- Scientific Data Processing :
Data processing in scientific and engineering problems is termed as scientific data processing. Basically, it is the application of computer simulation and other forms of computation to problems in various scientific disciplines. It is characterized by relatively little input and output but extensive internal computation. It emphasize on high speed internal processing but may have limited input and output capabilities.
- Real time Data Processing :
There are many types of large applications that may require the real time data processing. In this, the result is presented at the same time when the data enters. We can easily analyze this type of data processing in the stock market and currency trends. The technology which is mostly used in real time data processing is stream processing.
Advantages of Data Processing :
- Highly efficient
- High speed
- Reduces errors
Disadvantages of Data Processing :
- Large power consumption
- Occupies large memory
- The cost of installation is high
- Wastage of memory