The data analysis process for generic qualitative inquiry is inductive and iterative, allowing the researcher to develop a deeper understanding of the social phenomena they are studying. The data analysis process includes coding, categorizing, developing themes, and interpreting data. There is software available to assist researchers, such as NVIVO or ATLAS.ti. However, the researcher must still do much of the data analysis manually. For example, the patterns and themes that emerge during the thematic analysis process could allow the researcher to develop a deeper understanding of the phenomena instead of relying on a preconceived hypothesis.

One of the challenges to researchers is the sheer volume of data to be analyzed. Fortunately, software such as NVIVO and ATLAS.ti will assist the researcher in managing the process. Other data analysis challenges include defining or identifying meaningful themes and considering the potential for bias during the interpretation phase of the data analysis process. Time-consuming because of its iterative nature, the generic qualitative inquiry can be more labor intensive.

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