Requirements for Section 1
The aim of this assignment is to demonstrate knowledge and understanding of contemporary research and applied developments in the rise of the data economy. In this regard write a report to:
– Critically review the contemporary literature to discuss the strengths and difficulties of adopting business analytics in a specific industry of your choice (e.g. Manufacturing, Healthcare, Retail, Telecommunication, Transport, Finance, etc.). Provide some interesting suitable examples as appropriate to support your arguments. (500 words)
– In the selected specific industry, give examples on descriptive, predictive and prescriptive analytics applications with structured and unstructured data. Present new applications instead of applications widely covered as a part of the module. (500 words)
– Discuss the specific differences between classification and clustering applications for data analytics in your selected specific industry. (150 words)
The report should be well structured into different logical sections (including References at the end) and you should make sure that you write in a focused manner. You can add a short executive summary in the end highlighting the key discussions and findings which will not count in the word count. Your report should be typed with font size 12, and 1.5 line spacing. [55%]
Requirements for Section 2
(a) James Russon owns a medium sized lamb farm within the UK. He wants to improve the operational efficiency at his premises and streamline the flow of product (lamb), information (demand of lamb from clients) and finance thereby attaining a competitive edge against its rival farms.
Select one of the data technologies (RFID, Cloud Computing Technology, Blockchain) taught within this module and provide in-depth analysis about how it can be employed by James to generate competitive advantages.
(b) James has the monthly data of lambs sold to one of his major clients as listed below:
S.No. Month Lambs Sold
1 January 20
2 February 23
3 March 26
4 April 21
5 May 24
6 June 22
7 July 28
8 August 27
9 September 23
10 October 20
11 November 26
(i) Employ 6-months moving average to forecast the number of lambs to be sold in December.
(ii) Use exponential smoothing with alpha=0.3 and (assume forecast for January is 21) to forecast the number of lambs sold in December.
(iii) Calculate Mean Absolute percentage error for the forecasting techniques employed in (i) and (ii) and investigate, which one is more precise.
Adhere to the word limit (950 words). Academic references should be from journal articles, government reports, leading news outlets and consultancy (KPMG, Deloitte, etc.) reports published in recent 10 years and should be formatted in line with Harvard referencing.
You can add a short executive summary highlighting the key discussions and findings. Please note that executive summary will be excluded from word count. Your report should be typed with font size 12, and 1.5 line spacing. [45%]
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