Data is the most crucial part of any study. The data can be intrinsic or extrinsic. It depends on the subject and the mode of data collection. As a researcher and analyst, you always want to gather data for relevant topics and then assemble it.
The first thing any researcher or analyst does when he or she sees data is to find the pattern in it. They look for a definite pattern, connection, and relationships among the chunks of data obtained.
This is done to extract meaning from the data collection. Qualitative Data Analysis is the next step after collecting data from various sources.
The data is analyzed by the researchers or analysts to obtain a meaningful result. The whole process of data analysis has devoted this task. Several data analysis process is known in present times.
The modes of data analysis depend on the type of research one is performing. The data analysis is done either quantitatively or qualitatively.
The qualitative data analysis is done by considering all areas of the collected data.
Here the data is interpreted and then evaluated to gain a meaningful result.
The results obtained here are highly essential to conclude the research work.
What is Qualitative Data Analysis?
Qualitative data analysis deals with the identification of the collected data to find out the relationship between it.
After this, data is examined and interpreted for obtaining a meaningful connection to establish a relationship among textual data formats. Further, it determines the patterns and themes of the data to get a good result. The analysis helps to answer all research questions very smoothly.
The qualitative data analysis alleviates the work of data interpretation.
The result is drawn out from the textual formats of data.
Please note that qualitative data analysis works throughout the analysis process of data.
It is continuous and cyclical along the length of the data evaluation process. The researchers and analysts do qualitative analysis to certain the task of drawing meaningful connections and relationships.
When doing qualitative analysis, observe keenly the pattern occurring in the data formats. It is a crucial step in the qualitative data analysis method.
Importance of Qualitative Data Analysis
Qualitative data is vital in knowing the frequency of traits and characteristics of a particular data case.
The qualitative data analysis helps the researcher or analysts form-data parameters to extract more massive data sets.
The researcher observes these data sets through qualitative data analysis. This type of data analysis allows researchers to extract data sets for the quantification process. Hence, we can say that qualitative data is the base of quantitative data.
In the case of market research also, qualitative data plays a significant role. It helps the market researcher to answer all questions related to their queries. The qualitative data answers all questions of market research with ease.
All questions related to issues and problems get answered by qualitative data analysis for resolving later.
In simple words, it is said that qualitative data is about the perception and emotions of people involved in the analysis. The same perceptions are taken into account in quantitative data analysis, where it gets documented for further research.
Moreover, qualitative data helps the marketer learn about their consumers’ perception of any particular topic. It allows the researcher or analyst to deal with the problem effectively and efficiently.
Types of Qualitative Data Analysis
Qualitative data resemble all non –numeric information that includes text documents, images, interview transcripts, notes, videos, and audio recordings. Further, the analysis method is divided into the following types:
1. Content Analysis
Here the data is categorized according to the verbal and behavior standards of data. The work is done through the classification and summarizing the data.
The tabulation of data is done after this. The analysis solely depends on the content of the data collected. Content analysis is usually done to extract responses from the interviews to conclude the relationships and patterns.
2. Narrative Analysis
This type of data analysis is done through the reformulation of the story formed by the respondents.
The story is formed by taking into consideration all facts and figures of data formats. In simple words, narrative analysis is the revision of primary data collected in the data analysis process. The stories are formed due to the connection and themes of all data sets.
Narration is done here by the experienced people by answering all research questions.
3. Discourse Analysis
In this type of data analysis, the process takes place through naturally occurring talk and contextual formats.
The data is taken into consideration for forming the base of analysis. The method focuses on the analysis of the social context of the data case.
The communication among the respondents is necessary here to establish the result. Discourse analysis also looks for the respondent’s day-to-day activities to conclude the results.
4. Framework Analysis
This qualitative analysis is the most advanced form of data analysis. Here, the contents are extensively studied to conclude the relationships among data.
The analysis method includes familiarization, identifying, coding, framework, charting, interpretation, and mapping.
The analysis is done through perfect channelize systems that frame the whole research work.
5. Grounded Theory Analysis
Here the single case is taken into consideration for making up the story.
It means the analysis starts with a single case, and then it starts correlating with each other. The story’s formulation takes place through a single case and then corresponds to the top more cases.
The analysis is good and can be implemented for better results. These types are widely used for establishing good qualitative data analysis.
Prominent researchers and analysts work on these methods to gain the analysis method.
Methods of Qualitative Data Collection
The data collection for qualitative data collection is exploratory in all terms.
It includes in-depth research and analysis on the respective topic. The collection method mainly focuses on getting the insights of the respective data sets for proper research work.
To gain such insights, the researcher digs into depth for the data collection in qualitative data analysis.
Following are some of the methods by which researchers and analysts do qualitative data analysis:
1. One-to-one interview of the people involved
This method is the most common way to get qualitative data for research.
The analysts can conduct these interviews for people involved in the case study and get all insights while interviewing them. The interviews can be formal, structured, or informal and unstructured.
It all depends on the need of the research work. In these interviews, the questions are mainly open-ended and do not include any personal questions.
2. Group discussions
To gain qualitative data for the research work, many researchers organize group discussions for people.
The group discussions are held on a particular topic about the research, and people present their opinions. The group should be of only 6 to 10 people.
Larger groups make the discussions unclear and clutter full.
This method relies on the previous, present reliable documents.
The researcher or analyst takes the help of record books to generate qualitative data for research work. All data found in these records and existing books are used in the new research work.
This method is less tedious than the former ones, as the records are existing beforehand. As a researcher, you can get these reliable data facts from relevant books and depositories.
4. By observations method
Observation is the best method to gain all real insight into the people involved in research work.
In this case, the researcher himself or herself got to the respondents and observed their qualitative data collection behavior.
The researcher keeps a keen eye on them for getting all insights about their traits and perceptions.
How Qualitative Data Analysis Methods Work?
Some steps of qualitative data analysis are followed for an effective analysis of the collected data. To draw a meaningful result out of the data texts, the qualitative analysis is done. Following steps are needed for the qualitative data analysis by any researcher and analyst:
1. The application and development of codes on the data
Here, coding means the categorization of the data. The collected data is categorized under some subcategories to make it distinct from one another. The codes can be a short phrase or a word.
The phrase a word represents the theme of the research carried on. All codes should be meaningful. As a researcher or analyst, you have to assign some meaningful context to the codes.
Don’t make any vague codes that don’t resemble your research work. Non- quantifiable codes are assigned like behavior, meanings, themes, etc.
The coding is done under these three types
- Open coding: This is the first step in the categorization of data. The raw data is collected and then assigned a specific name for it.
- Axial coding: The next step in coding is to establish links to raw data. This type of coding joins links to other categorized data and make the connection.
- Selective coding: The third step includes the formulation of stories from all categorized codes. This is the final step of coding that clears the picture of the collected data.
The coding can be done manually or through coding software like NVivo, HyperRESARCH 2.8, Max QDA, etc.
2. Identification of themes, patterns, and relationships in the collected data formats
There are no accurate ways to generate the findings of themes and relationships. Here, the analytical and thinking skills of the researcher play an essential role. It depends on the type of research one is carrying. So, there is no one way to find the themes and relationships in qualitative data analysis.
However, you can use a set of instructions to generate your findings using qualitative data analysis. These instructions are useful in finding the patterns, themes, and relationships within the sample group responses.
Following are the most effective methods of data interpretation in qualitative data analysis:
Word and phrase repetitions in the collected data formats
All researchers implement this method on the primary data to get the requisite pattern. They scan the data formats for repetitive words and phrases to get a perfect pattern.
Comparison of Primary and Secondary Data
Comparing the findings from the above steps is crucial. All Primary and Secondary data is compared to a better understanding of the research work. You can also compare all the Literature reviews to get the perfect relationship among the data formats. As a researcher or analyst, you can also ask your respondents for the comparison task.
Search the Missing Information in the Data Given
Do an extensive discussion on the missing part of the data. Not all data received is complete. So, please make a list of missing aspects of the data, and search for them. Organize discussions for getting all missing parts of the data to establish perfect relationships.
Comparison of the Findings to Metaphors and Analogues
To interpret the data qualitatively, you can compare your findings to the different data sets to get proper insights. The comparisons give a good insight into the interpretation of the data. The patterns and themes can be concluded by this method.
3. Summarizing your Data
This is the last step for the qualitative data analysis process. Here, you have to compile your data as per your findings for further work.
At this step, you have to link all research findings to your data collection. Summarize well to answer all related questions from the research point of view.
Compile your work using all links to the hypothesis, evaluation charts, etc. this step allows you to get the perfect analysis report of our work.
Summarizing your data is the last step, but the most important one. Without this, the data analysis work is incomplete.
Final Thoughts about Qualitative Data Analysis!
Data analysis is the most crucial aspect of any research work. They are used for every type of research work.
The weak analysis produces bad results. A bad analysis does not work on good research work. It always hinders your research work. It is mandatory to go through qualitative data analysis to make the research work effective.
Moreover, qualitative data analysis is way too simple to implement in your research work. So, it is always advised to choose your analysis method very efficiently.