61884 – Assessment 1 InformationSubject Code: DATA4000Subject

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1 Code: DATA4000Subject Name: Introduction to AnalyticsAssessment Title: Case StudyAssessment Type: Written assessmentWord Count: 2000 Words (+/-10%)Weighting: 30 %Total Marks: 30Submission: via TurnitinDue Date: Monday Week 5, 23:55pm AESTYour TaskComplete 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 InstructionsPart 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 arising from the case study.c) The type of analytics used, and how it was used to address that business problemd) The main challenge(s) of using this type of analytics to achieve a business objectivee) 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=7042. GE : Big Data, Machine learning And ‘The Internet of Energy’ https://www.bernardmarr.com/default.asp?contentID=1266Part 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 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, 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 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-drivenorganization.pdfImportant Study InformationAcademic Integrity PolicyKBS 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 AssessmentsSubmissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded.Study AssistanceStudents 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.Assessment Marking GuideCriteria Criteria NN (Fail)0%-49% P (Pass)50%-64% CR (Credit) 74%-65% DN(Distinction)75%-84% HD (HighDistinction)85%-100%Part A:CaseStudyAnalysis Analyse how analytics can enhance businessperformance and identify the challenges of integrating analytics into diverseindustriesIncorrect or incomplete interpretation of case study with referenceto the questionsLittle or no reference to the course material, methods and analytics applications Basic interpretation of case study with reference to thequestionsMinimum reference to the course material, methods and analytics applications Moderately supportedinterpretation of case study with referenceto the questionsReference to some of the course material, methods and analytics applications Well-supported interpretation of case study with reference to thequestionsReference to most of the course material,methods and analytics applications Well-supported and engaging interpretation of case study with reference to thequestionsReference to all key course material, methods and analyticsapplicationsA novel approach taken to the representation of the contentPart B:Role ofAnalytics Evaluate the role of analytics processes and procedures in solving business problems and conduct researchinto 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 ofbusiness applicationsConsideration of how analytics can solve business problems with limited examplesDescription of the different types of analytics and a consideration on how each can be used in business.Solid exploration of analytics solutions with reference to well-researchedcase studiesDescription of the different types of analytics and an illustration of how each can be used to address abusiness problemComprehensive exploration of analytics solutions with reference to wellresearched, relevant case studies Comprehensivedescription of the different types of analytics and a critical evaluation of how each can be used to addressa business problemConvincing and engaging exploration of feasible analytics solutions with reference to well-researched,detailed case studiesPart C:AnalyticsJobs 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 ofinformation 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 oftheir associated tasksStudent does not provide feasible recommendations for the type of analytics professionals required by a given scenarioundertaken by variousrolesStudent provides minimumrecommendations for the type of analytics professionals required by a given scenarioStudent provides adequate recommendations for the type of analytics professionals required by a given scenario undertaken byvarious rolesStudent provides solidrecommendationsfor the type of analytics professionals required by a given scenario analytics undertaken byvarious rolesStudent provides well supported recommendations for the type of analytics professionals requiredby a given scenarioComments:Assignment SubmissionStudents 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 any technical issues that may occur from incorrect file format upload. Uploaded files with a virus will not be considered as a legitimate submission. Turnitin will notify you if there is any issue with the submitted file. In this case, you must contact your lecturer via email and provide a brief description of the issue and a screen shot of the Turnitin error message.Students are also encouraged to submit their work well in advance of the time deadline to avoid any possible delay with Turnitin similarity report generation or any other technical difficulties.Late assignment submission penaltiesPenalties will be imposed on late assignment submissions in accordance with Kaplan Business School’s Assessment Policy.Number of days Penalty1* – 9 days 5% per day for each calendar day late deducted from the student’s total Marks.10 – 14 days 50% deducted from the student’s total marks.After 14 days Assignments that are submitted more than 14 calendar days after the due date will not be accepted and the student will receive a mark of zero for the assignment(s).Note Notwithstanding the above penalty rules, assignments will also be given a mark of zero if they are submitted after assignments have been returned to students.*Assignments submitted at any stage within the first 24 hours after deadline will be considered to be one day late and therefore subject to the associated penalty.If you are unable to complete this assessment by the due date/time, please refer to the Special Consideration Application Form, which is available at the end of the KBS Assessment Policy:https://www.kbs.edu.au/wp-content/uploads/2016/07/KBS_FORM_Assessment-Policy_MAR2018_FA.pdf

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