The Process of Data Analysis

The process of data analysis is comprised of five core processes that begin with data collection from a range of sources, compiling the raw data, disassembling, followed by assembling, interpreting the data into information and finally coming up with a conclusion based on the data collected so that it can be used as information. The process of compiling entails an interviewer collecting data from a variety of sources and then grouping it into a data pool for analysis (Nemeth and Michalconok 2017). This process involves interviewing individuals who have given their consent and the raw data is then transcribed into notes for better analysis, storage and for future reference.

The disassembling process involves categorizing the collected data into various codes depending on the various topics being analyzed by the researcher. This process enables the researcher identify various themes that aid in identifying the correct categories of the data collected (Nemeth and Michalconok 2017). The process of assembling on the other hand involves sieving through the data again in order to identify if any themes have not been captured during the data disassembling process. This ensures that important data is captured to be used interpretation stage, the researcher in the interpretation process.

At the interpretation stage, the researcher then sorts the data and tries to analyze the data with aim of using the data to explain phenomena that is being researched. This is where the results are analyzed to identify whether the null hypothesis is true or false. The collected data is analyzed through the inductive process of reasoning to compare the findings of the research with existing information and other statistical frameworks. Lastly, at the conclusion stage, the collected data is summarized into theorems and findings. Simply, the collected data is translated into information that can be used.

References

Nemeth, M., & Michalconok, G. (2017). The initial analysis of failures emerging in production process for further data mining analysis. 2017 21st International Conference on Process Control (PC).

http://doi.org/10.1109/pc.2017.7976215