Task 1. You are required to critically discuss the impact of Big Data integration on effective decision making. Your answer should display a thorough and extensive engagement with academic literature, and come to the informed judgements of what the impact of integration of Big Data had for the profitability of the company.
Task 2. You are required to critically evaluate the literature regarding the success or failure of Big Data adoption by the enterprise, and conclude with an informed judgement why the MNE was successful (or unsuccessful) in their integration of the Big Data approach.
The choice of question will be based on the case that you will choose. For example, for the company that successfully managed to increase sales by adoption of the Big Data it makes more sense to select Task 1. Alternatively, for unsuccessful cases, where the company failed to achieve their goals by integration of the Big Data you can select Task 2.
Both answers should demonstrate extensive engagement with academic literature.
Task 3 below is compulsory for all students (35 marks):
You are required to come to a judgement regarding the ability to provide the positive ROI (return on investments) for companies investing in Big Data analytics. Your answer should specifically show an engagement with the academic literature regarding both ROI and Big Data. Your answer should conclude with recommendations as to how the current managers of MNE must approach the integration of the Big Data analytics in their strategy.
Please note, that all tasks should be highly linked to the business case that you considered. It is absolutely essential to display good critical and analytical thinking skills. Discussion of the theory and practical case must be maturely related.
(70 marks total)
Part B. Reflective Statement
Students must submit a Statement of Learning of no longer than 1000 words in length which summarizes their learning experience on the module and their reflections on their module experience. The statement of learning should:
1. Reflect on the student’s ability to relate what they are learning in the classroom (lecture and seminar) to real world business activities, events or decisions. (15 Marks)
2. Effectively communicate the student’s own learning journey while on the module, highlighting how they have engaged with the study of Big Data on a personal level through the module’s curriculum and assessment process (15 Marks)
The Statement of Learning should be a cohesive document rather than a week-by-week summary. Students should not in their statement be repeating the content of delivery, seminars activities, and essay, but instead be referring to them as evidence to reinforce their points.
Students are allowed to enclose Appendices with their personal Blog posts, Tweets, Facebook posts (screen shots) to evidence their engagement with Big Data.
