Research Discussion 11- Data Analysis Spiral

Running head: SPIRAL DATA ANALYSIS

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SPIRAL DATA ANALYSIS 2

Spiral data analysis

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Yes, I think the data analysis spiral is concise as it captures all the qualitative analysis involved in efforts to have the information comprehended and the phenomena understood (Creswell, 2007). The data analysis via spiral makes it easy to synthesis data and reconnects the coming knowledge to what is already known. To effectively manage the data, there is a need to have the coding done, which is present when it comes to the spiral data analysis hence making it too concise.

According to Creswell, he urged that the research design refers to the pattern that is followed by the researcher in attempts to collect, interpret, analyze, and also interpret the information or data .for effectiveness, the way the data was mined and analyzed is important (Creswell, 2007). This calls for the need to have the describing and classifying as a separate coding and cause the interpretation to be its loop. Data when collected or when mined can mean anything; it must be described to be understood by the user. Description of data makes it easy to understand the reading and the purpose of the data mined (Hennink et al., 2020). When the researcher gets the description of the data, one is in a better position to put it into, especially if it fits into the intended purpose of data mining and meets the intended target. Data description captures some vital aspects, including the motive behind the data mining, the possible usage, analysis, and strengths and weaknesses. Data classification is another essential component in data analysis, and it is completely different from the description. Classification makes it easy to gather data that are closely related or contain the same features or characteristics. Researchers dealing with data must t all times story to get engagements with the data via the reflections and the readings; hence a need to have the mined data described, interpreted, and classified. Data i=mining and analysis is never complete without having the representations or the visualization of the data meant for others. The many varied ways in which data can be represented and be described make it be its loop as there is room for varied interpretation and representation. The data description and interpretation process under which data reviews can be done as a process curtesy of some predefined processes. Interpretation assists in assigning meaning to data and also concluding relevantly. Results of the data analysis are taken and be involved in other tasks.

References

Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five approaches. SAGE.

Hennink, M., Hutter, I., & Bailey, A. (2020). Undefined. SAGE.