INTRODUCTION
MEANING AND DEFFINITION
Data Processing is a process of converting data into the information and it can also convert information into a data. It means Data Processing can convert any data from one format to another. By means of various sources, customers give their opinions as data.
Data Processing System is a system which processes data which has been captured and encoded in a format recognizable by the data processing system or has been created and stored by another unit of an information processing system.
Data is defined as any collection of facts. Thus, sales reports, inventory figures, test scores, customers’ names and addresses, and weather reports are all examples of data. Note that data may be numerical (e.g, inventory figures and test scores) or they may be numerical (e.g. , names of students and addresses, drawings).
Many businesses are venturing to take immense advantage of it as data processing is an essential ingredient in the market research. Data are facts or figures through which one can jump into the conclusion. By gathering plentiful data, Companies then utilize that information for swelling their revenue or for cutting-down the price.
AREA OF DATA PROCESSING
Data processing is the manipulation of data into a more useful form. It is the modern name for paperwork and involves the collecting, processing, and distributing of facts and figures to achieve a desired result. Data processing includes not only numerical calculations but also operations such as the classification of data and the transmission of data from one place to another. In general, we assume that these operations are performed by some type of machine or computer, although some of them could also be carried out manually. Data processing system refers to the equipment or devices and procedures by which the result is achieved.

DATA PROCESSING CYCLE 1. INPUT: In this step the initial data, or output data, are prepared in some convenient form for processing. The form will depend on the processing machine. For example, when electromechanical devices are used, the input data are punched on cards; but if electronic computers are used, the input data could be recorded on any of several types of input medium, such as cards, tapes, disks, and so on. 2. PROCESSING: In this step the input data are changed, and usually combined with other information, to produce data in more useful form. Thus, paychecks may be calculated from the time cards, or summary of sales for the month may be calculated from the sales orders. The processing step usually involves a sequence of certain basic processing operations. 3. OUTPUT: Here the results of the preceding processing steps are collected. The particular form of the output data depends on the use of data. For example, output data may be paychecks for employees, a printed summary of monthly sales for management, or simply data to be stored for further processing at a later date. INPUT PROCESS OUTPUT

FIVE STEP APPROACH TO DATA PROCESSING:
1. EDITING – To determine the relevance of data is a crucial step in a data processing. Once the data has been accumulated from the different sources, the relevance of the data is been tested-out then. All the inappropriate data is taken out and only the relevant information is been kept.
2. CODING – All the needed information would be in a random order. Therefore, it needs to be aligned into a particular system so that it is unproblematic to comprehend it. This method other than Coding, is also called as ‘netting' or ‘bucketing' which necessitates certain codes.
3. DATA ENTRY – Data is entered into the software that does the eventual cross tabulation. After the decision has been made on a code, edited data is than entered into the software.
4. VALIDATION – Validation is the second phase of ‘cleaning' in which thorough quality-check is been done. Data is double-checked so as to ensure that the process has been done infallibly.
5. TABULATION – Final step is the production of the end product which is tabulated in a systematic format so that thorough analysis can be done.

MERITS OF DATA PROCESSING:- * Data Processing is a process of organizing and controlling the large amount of information. * It is helpful to manage the important information in synchronized manner. Business data processing includes processing data of accounting, marketing, manufacturing and other department. * Reduced Paper Work: It is the one of the advantages of processing information. It helps organization to cope with increased problem of paper management and handling. Information is available digitally so there is no need to search through bunches and get particular file. * Easier Report Making: You can gather processed facts and figures in very little time and arrange such in appropriate manner that helps executives in making quick analysis. There are also pre-defined reports that help professionals in making reports quickly and easily. * Cost Reduction: The cost of data processing is much lesser than the cost of managing and maintaining paper documents. Organizations also decrease the cost of stationery such as photo copy and mailing by using digital information and email system. * Improved Performance: The performance of staff is the base thing for any organization to improve the profitability. Companies can increase the efficiency of personnel by offering them facilities and ease in work.
DEMERITS OF DATA PROCESSING:- * Technical and Mechanical mistake. * Time factor * Equipment is expensive * Much money required to design special computer system * Important data will be lost if computer breaks down

OBJECTIVE OF DATA PROCESSING * Provide the data in accurate and easier form. * Provide any data in less time period. * Provide help to manage the important data/Information. * Enhance working condition. * Store the data for future purpose.

APPLICATIONS OF DATA PROCESSING
Online Transaction Processing (OLTP) systems are one of the most common data processing systems in today's enterprises. Classical examples of OLTP systems are order entry, retail sales, and financial transaction systems.
OLTP systems are primarily characterized through a specific data usage that is different from data warehousing environments, yet some of the characteristics, such as having large volumes of data and lifecycle-related data usage and importance, are identical.
The main characteristics of an OLTP environment are: * SHORT RESPONSE TIME
The nature of OLTP environments is predominantly any kind of interactive ad hoc usage, such as telemarketers entering telephone survey results. OLTP systems require short response times in order for users to remain productive. * SMALL TRANSACTIONS
OLTP systems normally read and manipulate highly selective, small amounts of data; the data processing is mostly simple and complex joins are relatively rare. There is always a mix of queries and DML workload. For example, one of many call center employees retrieves customer details for every call and enters customer complaints while reviewing past communication with the customer. * DATA MAINTENANCE OPERATIONS
It is not uncommon to have reporting programs and data updating programs that need to run either periodically or on an ad hoc basis. These programs, which run in the background while users continue to work on other tasks, may require a large number of data-intensive computations. For example, a University may start batch jobs assigning students to classes while students can still sign up online for classes themselves. CONCLUSION * In most of the study the maximum person has been depend on the data processing system. * The data processing system are used at any time at any place and provide the data as according to need of the one person to another person. * The data processing system has been easily used in any work. * The maximum people are depend on electronic data processing system in any work * It helps organization to cope with increased problem of paper management and handling. Information is available digitally so there is no need to search through bunches of files and get the particular file.