Instruction to Candidates:

1. 1. Answer ALL questions
2. This is an open book examination; student is not allowed to transcribe directly (cut and paste) any material from another source into their submission.
3. The Turnitin similarity for this module is 20% overall and lesser than 1% from a single source excluding program source codes.
4. Severe disciplinary action will be taken against those caught violating assessment rules such as colluding, plagiarizing or transcribing.
5. The final assessment answers handed in should be within 5 -18 pages in total for non programming modules, with a spacing of 1.5 and a font of 12pt Times New Roman.
6. Submission link is here. (Do not submit the question paper)
7. The breakdown of exam questions by Module Learning Outcome(s) and its associate weightage is as follows:

8. Start each answer on a separate page.
9. Complete the front cover of the examination answer booklet and question paper. Write the question numbers attempted on the front cover of the answer booklet.

Answer ALL Questions (40 Marks)

Case Study – Big data technologies-based application is used to process, analyse and store the supply chain industry data.

The ever-increasing importance of supply chain industry has brought together numerous challenges. Specifically, challenges are in collecting, processing, analysing, and storing of data. These are due to the digitalization and automation devices have generate huge amount of data in the supply chain’s applications.

The supply chain industry applications collect data from multiple participants such as manufacturers, retailers, vendors, etc. The data is useful for planning, sourcing and development, execution, delivery and return of products.

Currently, most of the supply chain applications still utilize traditional data processing systems to monitor and manage the real-time logistics tracking such as for sales numbers, inventory levels, delivery time, vendor, and shipping details, to name a few. In addition, most of the applications do not employ machine learning algorithms for prediction in the supply chain applications.

Based on the above case study, answer the following questions.

1. Discuss any FIVE (5) data processing and analysis problems associated with traditional supply chain applications.
(5 Marks)

2. Based on the above case study, propose a big data technologies and cloud-based application, detailing each component of the application in an appropriate diagram. The proposed application must include machine learning algorithm for analysing supply chain application’ data. (15 Marks)

3. Provide FIVE (5) justifications for selecting the big data and cloud technologies in reference to the answers given in (2). (10 Marks)

4. Evaluate FIVE (5) disadvantages of proposing the big data and cloud technologies in reference to the answers given in (2). (5 Marks)

5. Recommend the relevant solutions to mitigate the disadvantages as evaluated in (4). (5 Marks)