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Data Coding
Data Coding

Data Coding in Research Methodology

Data coding in research methodology is a preliminary step to analyzing data. The data that is obtained from surveys, experiments or secondary sources are in raw form. This data needs to be refined and organized to evaluate and draw conclusions. Data coding is not an easy job and the person or persons involved in data coding must have knowledge and experience of it.

What is a code?

A code in research methodology is a short word or phrase describing the meaning and context of the whole sentence, phrase or paragraph. The code makes the process of data analysis easier. Numerical quantities can be assigned to codes and thus these quantities can be interpreted. Codes help quantify qualitative data and give meaning to raw data.

What is data coding?

Data coding is the process of driving codes from the observed data. In qualitative research the data is either obtained from observations, interviews or from questionnaires. The purpose of data coding is to bring out the essence and meaning of the data that respondents have provided. The data coder extract preliminary codes from the observed data, the preliminary codes are further filtered and refined to obtain more accurate precise and concise codes. Later, in the evaluation of data the researcher assigns values, percentages or other numerical quantities to these codes to draw inferences. It should be kept in mind that the purpose of data coding is not to just to eliminate excessive data but to summarize it meaningfully. The data coder should ascertain that none of the important points of the data have been lost in data coding.

Coding Examples

Few examples are mentioned here to understand the data coding in a better manner.


“I prefer to shop from a store that provides a large inventory of the same product, every brand and every style in that product range. Usually in these stores you get maximum range of products you want to purchase. You get profits through deals and sales.”

The data coder can assign different codes to what the respondent narrated above. These codes might be as following;

“Preference for horizontal markets”

“Horizontal integration”

“Shopping preference”

Preliminary codes

When data coder assigns codes to the observed data, he cannot manage to assign well-refined codes in the first instance. He has to assign some preliminary codes first so that the data has become concise. He later on, further refines the codes to get the final codes. It must be kept in mind that codes are not the final words or phrases on the basis of which evaluation will be made. The researcher will filter the preliminary codes and then the final codes. He needs a pattern on the basis of which he can categorize the human behavior, action or likes and dislikes.

Final codes

The final codes will help you observe a better pattern in the data. This pattern is necessary to reach the final evaluation or analysis stage of the data. The final codes in data coding mean finding out meaningful words and phrases from the observed data. The respondents often do not choose meaningful words in their responses. The coder needs to extract the meaning out of the respondent’s wording. The codes in their final stage are like topics and themes, these themes generate a whole discussion to get the final results. Sometimes the interviewer or the observer writes down some codes as he observes the behavior of the respondent. Such codes are really worthy in the research because these codes cannot be derived from the written responses that the respondents provide. The data coder should look for the verbs and the actions that the respondent has mentioned in the text. He should also observe the behavior and where ever possible derive codes. One thing should be kept in mind that qualitative data analysis is all about finding out the meanings and interpretations, so the coder should have an eye for such things.


The codes are given meaningful names and they are put in categories. These categories help refine the research a lot. When data is coded again and again, it get refined. The refined data itself leads to patterns and themes. The patterns are the key to find out the true results of the research. These patterns or categories determine where does the large amount of the data inclines.



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