DATA4000_T2_2022_Assessment_01
Page 1 XXXXXXXXXXKaplan Business School Assessment Outline
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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: Tuesday Week 5, 23:55pm AEST
Your Task
Complete Parts A to C below by the due date.
Consider the ru
ic 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.
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Assessment Instructions
Part A: Case Study Analysis (700 words, 10 marks)
Instructions: Read the following two case studies. For each case study,
iefly describe:
a) The industry to which analytics has been applied
) A potential and meaningful business problem to be solved
c) The type of analytics used, and how it was used to address that potential and meaningful
usiness problem
d) The main challenge(s) of using this type of analytics to achieve your business objective (from
part b)
e) Recommendations regarding how to be assist stakeholders with adapting these applications
for their business.
1. Transforming customer experience with AI and Machine Learning – Telecoms with
Ericsson
https:
www.ericsson.com/en
log/2021/3/transforming-customer-experience-with-ai-and-
machine-learning
2. Artificial Intelligence in the Healthcare Industry
https:
www.acc.com
esource-li
ary/artificial-intelligence-healthcare-industry#
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.
https:
www.ericsson.com/en
log/2021/3/transforming-customer-experience-with-ai-and-machine-learning
https:
www.ericsson.com/en
log/2021/3/transforming-customer-experience-with-ai-and-machine-learning
https:
www.acc.com
esource-li
ary/artificial-intelligence-healthcare-industry
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Part C: Developing and Sourcing Analytics Capabilities (800 words, 12 marks)
Instructions: You are the Chief Analytics Officer for a large multinational corporation in the
communications sector with operations that span 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).
The business 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 of your own that addresses the following key
points:
1. How do we best ingrain analytics into the organisation’s 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?
To help you draft this report, you should review the following working paper from Accenture:
https:
pdfcoffee.com/accenture-building-analytics-driven-organization-pdf-free.html
The report is prepared for senior management and the board of directors. It must reflect the needs
of your organization and the sector you operate in (communications).
https:
pdfcoffee.com/accenture-building-analytics-driven-organization-pdf-free.html
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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/cu
ent-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
esources on the MyKBS Academic Success Centre page. Click here for this information.
http:
www.kbs.edu.au/cu
ent-students/student-policies
https:
elearning.kbs.edu.au/course/view.php?id=1481
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Assessment Marking Guide
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DATA4000
Assessment 1
Ru
ic
30
Has demonstrated limited achievement:
Has achieved all or most of:
Part A: Case Study Analysis - Analyse how analytics can enhance business performance
and identify the challenges of integrating analytics into diverse industries
XXXXXXXXXX /10
• Inco
ect or incomplete interpretation
of case study with reference to the
questions
• Has not analysed how analytics can
enhance business performance
• Little or no reference to the course
material, methods and analytics
applications
• No originality, minimal effort
• Well-supported and engaging
interpretation of case study with reference
to the questions
• Has clearly analysed how analytics can
enhance business performance
• Reference to all key course material,
methods and analytics applications
• A novel approach taken to the
epresentation of the content
3
3
2
2
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
0-3 4-8 /8
• 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
• 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
4
4
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Part C: Analytics Jobs - Investigate existing analytics jobs and identify the type of
analytics involved in their associated tasks
XXXXXXXXXX /12
• Student is not able to identify the types
of analytics undertaken by various
oles
• Student does not provide feasible
ecommendations for the type of
analytics professionals required by a
given scenario
• Student comprehensively identifies the
types of analytics undertaken by various
oles
• Student provides well supported
ecommendations for the type of analytics
professionals required by a given scenario
6
6
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Assignment Submission
Students must submit their individual analysis via Turnitin on Tuesday 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 inco
ect 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
ief description of the issue and a screen
shot of the Turnitin e
or 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 penalties
Penalties will be imposed on late assignment submissions in accordance with Kaplan Business School’s Assessment Policy.
Number of
days
Penalty
1* - 9 days 5% per