What Is Data Processing in Market Research

Data Processing in research is the assortment and interpretation of an informational index into significant, usable data. Through this cycle, a specialist, information designer, or information researcher takes crude information and converts it into a more intelligible configuration, like a diagram, report, or graph, either physically or through a computerized device.

Data processing, control of information by a PC. It incorporates the change of crude information to machine-lucid structure, stream of information through the CPU and memory to yield gadgets, and designing or change of result. Any utilization of PCs to perform characterized procedures on information can be incorporated under information handling.

Data Processing is worried about altering, coding, arranging, classifying and outlining, and charting research information. The substance of information handling in research is information decrease.

Its Importance:

The importance of data processing incorporates expanded efficiency and benefits, better choices, and more precision and unwavering quality. Further expense decrease, ease away, dissemination and report making followed by better investigation and show are different benefits. There are many other services like data processing that come under Market Research like Survey Programming, Data Visualization, and Translation Services.

The four main stages of the data processing cycle are:

• Data collection- Data Collection in Marketing Research is a detailed process in which a planned search for all relevant data is made by the researcher.
• Data input- Market research data entry allows compilation, sorting, and organizing of the data to gain a detailed and comprehensive look into market research information.
• Data processing- Data processing in research is the collection and translation of a data set into valuable, usable information.
• Data output

Objectives of Data Processing:

The following are the objectives of data processing:

1. To provide mass storage for relevant data.
2. To make easy access to the data for the user.
3. To provide prompt response to user requests for data.
4. To eliminate redundant data.
5. To allow multiple users to be active at one time.
6. To allow for growth in the database system.
7. To protect the data from harm like physical and unauthorized access.