DATA4000_T3_2020_Assessment_1 Page 1 XXXXXXXXXXKaplan Business School Assessment Outline Assessment 1 Information Subject Code: DATA4000 Subject Name: Introduction to Business Analytics Assessment...

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DATA4000_T3_2020_Assessment_1 Page 1 Kaplan Business School Assessment Outline Assessment 1 Information Subject Code: DATA4000 Subject Name: Introduction to Business Analytics Assessment Title: Individual Case Study Assessment Type: Written assessment Word Count: 2000 Words (+/-10%) Weighting: 30 % Total Marks: 30 Submission: via Turnitin Due Date: Monday Week 5, 23:55pm AEST Your Task Complete Parts A to C below by the due date. Consider the rubric at the end of the assignment for guidance on structure and content. Assessment Description • You are to read case studies provided and answer questions in relation to the content, analytics theory and potential analytics professionals required for solving the business problems at hand. • Learning outcomes 1 and 2 are addressed. Assessment Instructions Part A: Case Study Analysis (700 words, 10 marks) Instructions: Read the following two case studies. For EACH case study, briefly describe: a) The industry to which analytics has been applied. b) A business problem arising from the case study. c) The type of analytics used, and how it was used to address that business problem d) The main challenge(s) of using this type of analytics to achieve a business objective e) Recommendations regarding how to execute the development and deployment of analytics in a way that maximises acceptance and buy-in from stakeholders. 1. Big Data for Consumers: The Internet of Things revolution https://www.bernardmarr.com/default.asp?contentID=704 2. GE Power: Big Data, Machine learning And ‘The Internet of Energy’ https://www.bernardmarr.com/default.asp?contentID=1266 Page 2 Kaplan Business School Assessment Outline Part B: The Role of Analytics in Solving Business Problems (500 words, 8 marks) Instructions: Describe two different types of analytics (from Workshop 1) and evaluate how each could be used as part of a solution to a business problem with reference to ONE real-world case study of your own choosing. You will need to conduct independent research and consult resources provided in the subject. Part C: Developing and Sourcing Analytics Capabilities (800 words, 12 marks) Instructions: You are the Chief Analytics Officer for Telekonika, the largest telecommunications company in South East Asia and Latin America. The organization is undergoing significant transformations; it is scaling back operations in existing low revenue segments and ramping up investments in next generation products and services - 5G, cloud computing and Software as a Service (SaaS). Telefonica is keen to develop its data and analytics capabilities. This includes using technology for product innovation and for developing a large contingent of knowledge workers. To prepare management for these changes, you have been asked review Accenture’s report (see link below) and publish a short report that addresses the following key points: 1. How do we best ingrain analytics into our decision-making processes? 2. How do we organize and coordinate analytics capabilities across the organization? 3. How should we source, train and deploy analytics talent? 4. Discuss the key success factors that underpin and define an organisation’s journey toward becoming analytics driven. To help you draft this report, you should review the following working paper from Accenture: https://www.accenture.com/us-en/~/media/accenture/conversion- assets/dotcom/documents/global/pdf/industries_2/accenture-building-analytics-driven- organization.pdf Page 3 Kaplan Business School Assessment Outline Important Study Information Academic Integrity Policy KBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy. What is academic integrity and misconduct? What are the penalties for academic misconduct? What are the late penalties? How can I appeal my grade? Click here for answers to these questions: http://www.kbs.edu.au/current-students/student-policies/. Word Limits for Written Assessments Submissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded. Study Assistance Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Click here for this information. Page 4 Kaplan Business School Assessment Outline Assessment Marking Guide Criteria Criteria NN (Fail) 0%-49% P (Pass) 50%-64% CR (Credit) 74%-65% DN (Distinction) 75%-84% HD (High Distinction) 85%-100% Part A: Case Study Analysis Analyse how analytics can enhance business performance and identify the challenges of integrating analytics into diverse industries Incorrect or incomplete interpretation of case study with reference to the questions Little or no reference to the course material, methods and analytics applications Basic interpretation of case study with reference to the questions Minimum reference to the course material, methods and analytics applications Moderately supported interpretation of case study with reference to the questions Reference to some of the course material, methods and analytics applications Well-supported interpretation of case study with reference to the questions Reference to most of the course material, methods and analytics applications Well-supported and engaging interpretation of case study with reference to the questions Reference to all key course material, methods and analytics applications A novel approach taken to the representation of the content Part B: Role of Analytics Evaluate the role of analytics processes and procedures in solving business problems and conduct research into existing business cases where analytics is being used Inadequate description of analytics types and/or inadequate explanation of how analytics could be used as part of a business problem with minimal research conducted Description of the different types of analytics in a basic way with limited consideration of business applications Consideration of how analytics can solve business problems with limited examples Description of the different types of analytics and a brief consideration on how each can be used in business. Solid exploration of analytics solutions with reference to well-researched case studies Description of the different types of analytics and an illustration of how each can be used to address a business problem Comprehensive exploration of analytics solutions with reference to well- researched, relevant case studies Comprehensive description of the different types of analytics and a critical evaluation of how each can be used to address a business problem Convincing and engaging exploration of feasible analytics solutions with reference to well-researched, detailed case studies Part C: Analytics Jobs Investigate existing analytics jobs and identify the type of analytics involved in Student is not able to identify the types of analytics undertaken by various roles Student identifies minimum amount of information relating to the types of analytics Student identifies some of the types of analytics undertaken by various roles Student identifies most of the types of analytics Student comprehensively identifies the types of Page 5 Kaplan Business School Assessment Outline their associated tasks Student does not provide feasible recommendations for the type of analytics professionals required by a given scenario undertaken by various roles Student provides minimum recommendations for the type of analytics professionals required by a given scenario Student provides adequate recommendations for the type of analytics professionals required by a given scenario undertaken by various roles Student provides solid recommendations for the type of analytics professionals required by a given scenario analytics undertaken by various roles Student provides well supported recommendations for the type of analytics professionals required by a given scenario Comments: Page 6 Kaplan Business School Assessment Outline Assignment Submission Students must submit their individual analysis via Turnitin on Monday of Week 5 at 23:55pm AEST. This file must be submitted as a PDF document to avoid
Answered Same DayDec 08, 2021

Answer To: DATA4000_T3_2020_Assessment_1 Page 1 XXXXXXXXXXKaplan Business School Assessment Outline Assessment...

Taruna answered on Dec 10 2021
151 Votes
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Question One: Case Study One
(A)
    In the provided case study one entitled Internet Things of Evolution; the predictable theory of analytics has been used to develop the gadget of measuring the thermostat of room by smart management of the user behavior. The development of the instrument is likely to predict what is about to happen—one of the basic norms of predictable analytics is that it gives idea of the future—and
in this context, the Nest Thermostat is possibly the first attempt to provide exact temperature of the room which is set upon the preferences of the user. The instrument records smartly the behavior of the user and with AI application, processes the choices by its own. Nest is developing this product for the tech savvy kind of professionals who wish to work and live smartly due to the lack of time for their personal and professional space, at both levels.
(B)
    The business problem that arises from this case study is relatable to the challenges confronted by Nest here; the issue of making this product popularize among people is one of the key drivers of success to it. At the same time, it might be typical to make sure—or rather, to ensure the highly professional individuals that the product is unique and it can fulfill their demands—that the alignment of the consumer interest is done with the product itself. It has to compete with the products standing in the same line.
(C)
Basically, as per the observation of the case study, a few challenges related to it might include the innovation as the key to the rise of competency level. The product in itself is operational on internet and there are already several gadgets that are similar to the present one.
(D)
Also, not always, the accurate data projections of temperature are received by the any of the gadgets. There is a control line of difference and based on these differences, the product might show a range of room’s thermostat. Also, the product seems to have covered the limited premium range of buyers so, earning ‘good profits’ from it will be complicated.
Case Study Two
(A)
    The case study observation of GE Power and the use of innovative data feeding in the distribution of sustainable energy is the core essence of the descriptive analytics, the technique used by the company. In the context of looking at the conventional approach of distributing power, the company’s manager Bell perceives the ‘Edison’ way as the older one than the grid way which the organization is looking forward to.
(B)
The comparison of the two results in the fact that the to supplicate the needs and expectations of the humans to have seamless supply of energy, especially for developing regions of the world, it is necessary to have power options that are running on gird, controlled by the precision and accuracy of the data network. It is more like taking love feed of the requirement and supplying the same with the help of manually built grid. However, if seen closely, there are multiple dimensions of business issues that may arise from it. Starting from the most important one, in non-data feed based network, the chances of total black out are nominal because the energy supply is not based on grid.
(C)
When grid is formed, it is more like the network which is based on internet and efficacy of all units that are used in it. If one unit out of all fails by technical reasons, there is a total failure to supply from source to the end. This is one of the major issues that AI based power networks have to deal with.
(D)
    Secondly, the power operations at international level need to spend huge capital over developing their infrastructure into various regions of the world. It becomes even more typical than ever when this investment has to come in the developing parts of the world. A grid based network would not work over the existing instruments as it will require digitally driven tools and applications. Thus, replacing the existing system with the new one that is totally different will be cost expensive.
(E)
These points are implied in the concern of Bell when he talks about the expansion of services. Though he views immense possibilities by including AI based distribution in power networks, at the same time, he does mention that...
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