Data is a source of great information which can enable informed decision making for businesses. Data is divided into Quantitative Data and Qualitative Data. Qualitative data refers to those non-numerical, explanatory data. Herein, we will have a detailed look into the various methods of qualitative data analysis.

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Methods Of Qualitative Data Analysis

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Data is a source of great information which can enable informed decision making
for businesses. Data is divided into Quantitative Data and Qualitative Data.
Qualitative data refers to those non-numerical, explanatory data. Herein, we will
have a detailed look into the various methods of qualitative data analysis.
What is Qualitative Data Analysis?
The process of Qualitative Data Analysis includes analysing information or data
which aids in offering a certain level of understanding, explanation, and aids in
interpreting the patterns and themes included in textual data. To put it in general
words, qualitative data cannot be expressed in the form of numbers and is often
represented in words, observations, pictures, and symbols.

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Now coming to the methods used for analyzing qualitative data. There exist
numerous methods for analyzing and interpreting qualitative data. However, the
most popular and viable methods are listed below which includes 4 prominent
techniques viz.
1. Content Analysis
2. Narrative Analysis
3. Grounded Theory Analysis
4. Framework Analysis
5. Discourse Analysis
1.Content Analysis
This is the most popular type of qualitative analysis technique used by researchers.
It primarily includes interpreting the meaning of data and identifying the important
points in the content. It popularly includes analyzing the data published in the
social media field so as to understand and interpret the current patterns and trend in
social media.
Key purpose includes:
 Finding the important aspects of social media content through emails, chats,
comments, business emails, blogs, news, etc.
 To present them in an effective manner.
 The popular techniques under these are the conventional, summative and
directive approach.
2. Narrative Analysis
This type of data analysis is used for interpreting different types of stories. It
primarily aids in understanding how individuals form meanings in their lives so as
to explain their day to day workings and world. A narrative analysis uses units like
personal accounts, journals, autobiographical writing, letter writing, etc.

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Key purposes include:
 Aids in connecting past with the current situation.
 Understanding the interpretation of events.
 Gain knowledge about people, their culture and changes happening.
3. Grounded Theory Analysis
This method involves the generation of theory through the collection of data and its
analysis. The primary feature of this analysis is that it helps in focusing on theory
development. They are useful in interpreting a large quantity of data involving a
large unstructured group. The key methods include:
 Interpretation of texts
 Focus groups
 Interview with open-ended questions
 Participant observation
4. Framework Analysis
This type of data analysis method is used to manage and organize information
using the process of summarization. As the meaning of the word framework goes,
it helps in categorizing the data into a matrix comprising of rows (cases) and
columns (codes) and cells of summarized data.
Use:
 Helps in identifying similarities and differences in qualitative data
 Aids in drawing descriptive and explanatory conclusions
5. Discourse Analysis
It is widely in the field of linguistics that lays focus on the role of language in
building social reality. It thus deals with interpreting language through
communication and different types of texts.

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Use:
 Helps in exploring different texts, discourses, and its context
 Aids in drawing inferences
Choosing the appropriate qualitative data analysis technique will help achieve the
desired result along with gaining a deeper understanding of the data, its
explanation and interpretation.