Data Processing activities in Research

  1. Collection: Data originates in the form of events transaction or some observations. This data is then recorded in some usable form. Data may be initially recorded on paper source documents and then converted into a machine usable form for processing.  Alternatively, data may be recorded by a direct input device in a paperless, machine-readable form.  Data collection is also termed as data capture.
  1. Conversion: Once the data is collected, it is converted from its source documents to a form that is more suitable for processing. The data is first codified by assigning identification codes.  A code comprises of numbers, letters, special characters, or a combination of these.  For example, an employee may be allotted a code as 52-53-162, his category as A class and so on.  It is useful to codify data, when data requires classification.  To classify means to categorise, that is, data with similar characteristics are placed in similar categories or groups. For example, one may like to arrange accounts data according to account number or date.  After classification of data, it is verified or checked to ensure the accuracy before processing starts. After verification, the data is transcribed from one data medium to another.  For example, in case data processing is done using a computer, the data may be transformed from source documents to machine sensible form using magnetic tape or a disk.
  1. Manipulation: Once data is collected and converted, it is ready for the manipulation function which converts data into information. Manipulation consists of following activities:
  1. Sorting: It involves the arrangement of data items in a desired sequence. Usually, it is easier to work with data if it is arranged in a logical sequence. Most often, the data is arranged in alphabetical sequence.  Sometimes sorting itself will transform data into information.  For example, a simple act of sorting the names in alphabetical order gives meaning to a telephone directory.  The directory will be practically worthless without sorting. Business data processing extensively utilises sorting technique.  Virtually all the records in business files are maintained in some logical sequence. Numeric sorting is common in computer-based processing systems because it is usually faster than alphabetical sorting.
  2. Calculating: Arithmetic manipulation of data is called calculating. Items of recorded data can be added to one another, subtracted, divided or multiplied to create new data. Calculation is an integral part of data processing.  For example, in calculating an employee’s pay, the hours worked multiplied by the hourly wage rate gives the gross pay.  Based on total earning, income-tax deductions are computed and subtracted from gross-pay to arrive at net pay.
  • Summarising: To summarise is to condense or reduce masses of data to a more usable and concise form. For example, you may summarise Research findings by writing small notes in one or two pages. When the data involved is numbers, you summarise by counting or accumulating the totals of the data in a classification or by selecting strategic data from the mass of data being processed.
  1. Comparing: To compare data is to perform an evaluation in relation to some known measure. For example, business managers compare data to discover how well their companies are doing. They many compare current sales figures with those for last year to analyse the performance of the company in the current month.
    1. Managing the Output Results: Once data has been captured and manipulated following activities may be carried out :
  2. Storing: To store is to hold data for continued or later use. Storage is essential for any organised method of processing and re-using data. The storage mechanisms for data processing systems are file cabinets in a manual system, and electronic devices such as magnetic disks/magnetic tapes in case of computer based system.  The storing activity involves storing data and information in organised manner in order to facilitate the retrieval activity.  Of course, data should be stored only if the value of having them in future exceeds the storage cost.
  3. Retrieving: To retrieve means to recover or find again the stored data or information. Retrieval techniques use data storage devices. Thus data, whether in file cabinets or in computers can be recalled for further processing.  Retrieval and comparison of old data gives meaning to current information.
    1. Communication: Communication is the process of sharing information. Unless the information is made available to the users who need it, it is worthless. Thus, communication involves the transfer of data and information produced by the data processing system to the prospective users of such information or to another data processing system.  As a result, reports and documents are prepared and delivered to the users.  In electronic data processing, results are communicated through display units or terminals.
  1. Reproduction: To reproduce is to copy or duplicate data or information. This reproduction activity may be done by hand or by machine.

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