Data analysis strategies and methods

¶ … employed to be able to generate and analyze data that will ultimately answer the research question and its objectives. Both in the quantitative and qualitative domains of research, each approach under each domain have specific ways of collecting and analyzing data, all dependent on the purpose and appropriateness of the approach to answering the research question. In the case of qualitative research, while the general purpose of qualitative approaches is to cull out themes, ideas and insights about an event or phenomenon, it is still bound with a systematic manner of analyzing data. Qualitative data is especially susceptible to 'information overload,' and indeed it would help the researcher to develop a system through which data can be funneled, sifted through, and analysis based on its authenticity and to some degree, reliability, in answering the main question of the study or research.

In this paper, a review of the data analysis techniques will be discussed in the context of qualitative approaches. These approaches are the following: narrative research, phenomenology, grounded theory, ethnography, and case study. These approaches utilize data analysis and interpretation differently, mainly because each approach has a specific purpose or has an appropriate use depending on the focus of the study. Inevitably, this 'appropriateness of use' for each qualitative approach is linked with data analysis -- that is, data analysis responds to the use or purpose of the approach for the researcher. That is why each approach would provide different analysis and interpretations of an event or phenomenon, primarily because of the differences in the data analysis strategy or technique employed.

Narrative research draws it strength of generating insightful information through individual stories shared and explained in the context of a specific perspective or framework. Ultimately, narrative research brings into fore the importance of specific details in understanding a phenomenon. Authenticity of the experience is valued in this approach, which is why stories or personal histories are critical sources of information that the researcher would eventually use for data analysis. However, at the data analysis stage, the researcher would extract critical and insightful information, understand this information, and contextualize it to the framework or perspective of the study. Thus, narrative research functions as a tool to provide evidence about the truth or falsity of details or specific information concerning a particular event or phenomenon.

Phenomenology operates differently from narrative research, in that a higher number of informants or sources of information are utilized. Under this approach, personal histories or experiences of more than one individual are collected to have a deeper and at the same time, expanded understanding of the phenomenon under study. The higher the number of sources of information, the higher the chances of the researcher of generating an insight that would truly provide a meaningful understanding of the event or phenomenon. Like narrative research, phenomenology is also interested in specific details of the phenomenon; however, in phenomenology, the specific details are highlighted as this approach seeks to answer the "what" and "how" of an event or phenomenon.

Ethnography involves an understanding the lived experiences of a homogenous group. It shares similarities with narrative research and phenomenology, but the homogenous group component in its approach sets it apart from the others. Since it studies a homogenous group, the researcher's data analysis is more concerned about identifying specific socio-cultural elements in the group that are either recurring or extraordinarily different from the others. The identification of any deviations from the norm in the group is a critical factor that the researcher looks out for, as this provides validation about the consistency and strength of information that the researcher has generated while working with the group or population of interest.

Data analysis in case study research is similar with ethnography in that common themes are identified. However, it is also similar with narrative research analysis because it provides a specific scenario relevant to the phenomenon under study. It is through this scenario that analysis -- identification of themes and contexts in which these themes occurred -- will be conducted.