What is Data Processing : Types and Its Applications

The word data comes from the Latin language, which means the collection of raw information. The concept of data processing is all about processing raw data using a computer to obtain the desired meaningful output. The data can be processed either manually or automatically. The output data which is obtained after processing raw data is represented in various forms like, it can be either numeric form like 0-9, ., +, -, /, E, D, or character form which can be either string format like alphabetical format or alphanumeric format or graphical form like diagrams, charts, maps, which is based on the type of software used or the procedure used for processing data.

What is Data Processing?

The process of converting raw data using a medium like manual or automatic tools into meaningful output information is called data processing. The raw data like the number of students in a class, examination results, address, etc, which is given as input to the processor which uses certain procedures to manipulate the raw data and processes it to provide desired meaningful output. For example, If we purchase an item in a departmental store they provide us bill after purchasing, where the bill contains all the data items information like item details, customer name, phone number, address, time, bill amount, amount paid, tax, etc, all these put together forms an information, where this information is process form of data. The basic function of this processing is validation, sorting, summarization, aggregation, analysis, reporting, classification.



Different Types

There are three types of data processing, they are

Manual Data Processing

The data which is processed manually by human actions that are without using any tool is manual processing. Like for example manually writing or calculating a report manually and accurately is manual processing, manually verifying marks sheet, financial calculation, etc. The main disadvantage is that manual processing requires high labor costs, high time consumption, more errors, etc. Hence with this disadvantage, more advance tools have come where processing work is done automatically.

Electronic Data Processing (EDP)

It is also called as information services or systems. It processes the raw data through computers and programs using electronic communication. The processing work is very fast. The best example for electronic data processing is an ATM card, which is embedded with an electronic chip.

Real-Time Data Processing

It is a continuous process, which responds within seconds when the data input is given it gets processed and provides desired output data. For example, a person wants to draw a certain amount from his account using an ATM. As soon as he inserts the card and enters balance, he wants to draw along with ATM pin, the machine processes the transaction and updated his bank account balance online within a few seconds. The main advantage is time consumption.


Data Processing Cycle

This processing cycle is common to both manual and electronic processing. It is the series of steps for extracting information from raw data. There are 3 important stages in this processing they are,


The process through which data collected is transformed into a form that the computer can understand. It is the most important step because the correct output results depend on the given input data. The activities carried out in data input are of four stages, they are

Data Collection

Data collection is a very important step in processing where all raw facts are collected from various environments which should be well defined and accurate to processes it. Examples of data collection are land surveys, election polling.

Data Encoding

The process of converting raw facts into a form that is easier to provide as an input to the processing system is data encoding.

Data Transmission

At this stage, the data is sent to the processor and also to various components of the system

Data Communication

At this stage, the data is communicated between various processing systems.


This stage deals with manipulating raw data using various tools or software techniques to meaningful information. Many software tools are available to process large volumes of data within a short span of time. It can be explained in simple form in the following example of an automation data processing technique, the user writes a program to perform addition of two numbers, which contains set of instructions, this program is processed to the central processing unit which processes data based on the instruction provided. Now the software manipulates the data which provides instructions to process data and give meaningful expected information.


There are three different types of data manipulating techniques they are

  • Classification: Data has segregated accordingly into different groups and subgroups at this stage so that it would be easy to process.
  • Storing: At this stage, data is stored in a proper sequence so that it can be easily accessed when needed.
  • Calculation: At this stage, a number of operations are performed on the data to produce desired results.


At this stage, the data output which is obtained after processing is meaningful data, that is required for end-users. Output can be obtained in different forms like audio, video, report print, etc. The following are the activities carried out in out they are,

  • Decoding: The data which is encoded is decoded into the understanding format.
  • Communication: The output which is generated is distributed to various locations so that any user can access it at any time.
  • Retrieval: The data that is distributed and stored can be accessed by anyone at one’s convictions.

Storage Stage

The processed information is stored in virtual data memory for further use it is the important stage of the cycle because we can retrieve the data when required.

Data Processing in Research Area

The important steps mainly include in this processing are as follows,

  1. Questionnaire checking
  2. Editing
  3. Coding
  4. Classification
  5. Tabulation
  6. Graphical Representation
  7. Data Cleaning
  8. Data Adjustment
  • Questionnaire checking: The first step is to check if there are any questionnaires or no. Few of not acceptable questionnaires are incomplete or partial data, inadequate knowledge.
  • Editing data is identified if there are any errors in raw data so that if they are errors they can be edited and corrected.
  • Coding is the process of giving symbols so that responses can be placed into their respective groups.
  • Classification of data is based on classes like class interval, frequency or attributes like the city, the population is done for better understanding.
  • After classifying we tabulate the entire process in different relevant columns and rows.
  • Then represent them in graphical or statistical bar chart format.
  • After that, we check the entire data once again from first if there is any missing
    data, we add it up for consistency.
  • An additional concept of data adjusting is done as complementary to improve quality.


The advantages of data processing are

  • Highly efficient
  • Time-saving
  • High speed
  • Reduces errors


The disadvantages of data processing are

  • Large power consumption
  • Occupies large memory
  • The cost of installation is high
  • Wastage of memory.


The application of data processing is

  • In the banking sector, this processing is used by the bank customers to verify there, bank details, transaction and other details.
  • In educational departments like schools, colleges, this processing is applicable in finding student details like biodata, class, roll number, marks obtained, etc.
  • In the transaction process, the application updates the information when users request their details.
  • In a logistic tracking area, this processing helps in retrieving the required customer data online.
  • In hospitals patients, details can be easily searched.

This article describes the way raw data input processed when given as input to a processor, this raw data can be processed either using software or any other tool to obtain meaningful information. The important advantage of data processing is, one can retrieve data easily within a few seconds. Here in this article, we have seen the data processing cycle, processing in the research area, its advantages, disadvantages and its applications. Here is the question “How the data is processed in the e-commerce area?”.