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What is your subject about? A brief overview
This subject builds on the extensive review of the research topic in the area of Information Technology (IT) that students commenced in previous coursework subjects in the course. The subject requires students to reflect on their research plan, develop a detailed research proposal, with ethics approval as appropriate, defend their research proposal, and collect data using appropriate data collection techniques. Students will develop expertise relating to a major research issue and will have the opportunity to publish their research in academic conference proceedings or refereed journals.
How you are expected to engage with the subject
This is the last coursework subject that you have in DIT and is the continuation of the research projects that have commenced, particularly the project in ITC713. There are six topics in the subject:
- Generic Research Approaches;
- Empirical Research Methods;
- Statistical Basics, Data Analysis and Knowledge Discovery;
- Statistical Test and Analysis;
- Analysing, Interpreting and Synthesizing Research Results for the Presentation of Research Findings; and
- Reviewing and Publishing.
One of the main objectives of this subject is conducting the research project you have formulated in ITC713 and producing a publishable paper by the end of the session. Another important objective is to prepare a research proposal for your DIT studies. There are four assessment items that are designed to help you achieving these objectives.
Given that you have already prepared your research question, justification for the research, a literature review, and research methodology in Assignment 1 and Assignment 2, now it is the time to go for experimentation/data collection and data analysis.
Report on Experiment Results including Synthesizing/Analysing/Interpreting:
- Further develop your proposed solutions/algorithms/strategies in assignment 1. You will detail yo solutions/algorithms/strategies so that you can use them in your experiments.
- Carry out your experiments. You may need to write programs to code your technique and so existing techniques. Sometimes you may be able to use existing codes or simulation programs available freely to carry out your experiments. However, having a good programming skill can be advantageous to be a successful researcher in IT.
If you are unable to do the experimentation/data collection due to some reasons such as the ethics approval process, you will be required to generate some synthetic data based on your survey questions and your expectation on the survey responses OR based on your experimental design and your
expected results. On the other hand, if you are able to collect the data through experimentation/data collection then you need to proceed with the natural data.
- You will then need to analyse the data in different ways and present the results of your data analysis. You may also need to use statistical techniques such as confidence interval test, students t-test and chi-square analysis and data mining approaches such as decision trees and forests to discuss and evaluate the experimental results.
You need to present your experimental results in a nice, clear and comprehensible approach perhaps by using designed tables, graphs and figures.
- You need to do synthesizing analysis by comparing your results with those existing research in the similar topic to further describe the advantage and benefits from your research.
Big data has emerged to become widely recognized and adopted by companies worldwide. It has become very relevant in all types of organizations. In the case of businesses, big data plays an important role because its offers business value, as substantiated by the industry (Eric Boyd, Chandy, & Cunha Jr, 2010). In addition to this, business executives look for innovative means to maximize revenue for their organizations through the combined use of big data with cloud computing services (McAfee, et al. 2012). Big data and cloud has become a relevant topic in all types of organization. This relevancy is further justified by the industry as the trends show that cloud services adoption and integrating big data sources with internal data in organizations is on the rise worldwide (Wu, Zhu, Wu, Q. & Ding, 2014).
There are white papers and studies to show that organizations make use of big data to extract meaningful information which is further used to transform their business. Hence, for organizations that integrate conventional business analysis and reporting with big data and cloud technologies stand to gain more value by becoming more competitive (Davenport & Dyche, (2013). This report corroborates the claim that big data with clouds can truly be a business value enabler. To establish this statement primary research is conducted involving Australian firms that make use of big data in cloud for becoming more competitive and for increasing revenue. In big data processing clouds play an ideal role due to their resources and architecture built to handle large workloads (Mosco, 2015). The primary research is done using a survey questionnaire developed to collect data. Relevant synthetic data pertaining to this topic is derived from industry information sources to arrive at the data set. The data set is further analyzed using statistical methods and the results are presented to verify if the proposed hypothesis holds true. The results are interpreted and discussions provided in the report.
The method followed in this report is empirical research which makes use of primary data set. The data set is arrived from responses in the survey questionnaire. This study makes use of deductive and inductive research (Bryman, 2015) approaches. As business information systems implementation is a dynamic area undergoing constant changes (Laudon, Laudon & Brabston (2011). deductive and inductive approaches are considered. The research is based on scientific evidence and hence the need to use a survey questionnaire. The hypothesis is: 'Big data with cloud: A value enabler for businesses'. The hypothesis based on deductive approach and the experimental method verifies whether this hypothesis is true based on results.