Qualitative Research Philosophy

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Overview: This section explains the research philosophy, the literature survey for this research, data collection technique, data analysis approach and the overall process of the research. It started by gather the general insights that were relevant to the research; derived the information into a research topic; brief explanation about how the research was conducted, how the data was collected through experiment, how the data was analysed and concluded.

3.1. Research Philosophy
The main idea of the research was built upon a general insight that was gathered by reviewing a number relevant literature and research papers. Therefore the perspective of the research was an objective view, instead of subjective view, which was built on a personal
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It started by define the hypotheses; define relevant variables and set up a testing condition; data was collected by an experiment in controlled environments and using controlled variables (Dawson, 2009). The other testing technique was eliminated (such as action research, case study and survey) because those techniques were not suitable to this research.

Through the experiment, a quantitative and a numeric data were collected and treated as the primary data (Rosalia, 2015). Data analysis was presented in a statistical model along with the detail descriptions based on the experiment outcomes in order to answer the research question (Bryman, 2012). The secondary data was collected through the literature survey (Kumar, 2014).

A qualitative data collection (such as an interview, focus group and participant observation) was not applicable in this research because of these following reasons:
1. This research was about testing an existing theory, while qualitative approach is about establishing new theory (Bryman,
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Research Process
This research adopted the sequential process model, therefore the research was executed in a fixed and continuous sequences (Dawson, 2009).

1. Identify the wider knowledge
The wider insight about relational and non-relational database performance, particularly MySQL and Hadoop was gathered through the literature survey. By read textbooks, reviewing academic journals and research papers, I founded a gap in the performance of relational database compare to the non-relational.

2. Determine research topic
Research topic was derived from the understanding of query processing in MySQL and Hadoop, the database performance issues, performance tuning and the importance of database performance. Thus, it was decided to develop a comparative analysis to observe the effectiveness of the performance of MySQL (non cluster) and Hadoop in structured and unstructured dataset (Rosalia, 2015). Furthermore, the analysis included a comparison between those two platforms in two variance of data size.
3. Define research approach
A deductive reasoning was applied in a controlled experiment to verify the theory: In read and write operation, MySQL has a better performance compare to Hadoop in structured dataset, while Hadoop has a better performance compare to MySQL in unstructured dataset (Rosalia,
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