CQUniversity Unit Profile
ACCT28003 Business Analytics Techniques
Business Analytics Techniques
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The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

Overview

This unit introduces you to the world of data analytics in business. Business analytics uses software tools to produce strategic analyses of huge volumes of data stored in databases and data warehouses to support improved decision making. Business analytics is used in industry and government for basic reporting and descriptive analyses. Advanced predictive and prescriptive analytics also allow powerful insights to be generated. Some areas of application include improved understanding of customer behaviour, gauging sentiment on social media, analysis and prediction of factors influencing profitability and portfolio optimisation. This unit will provide you with foundation knowledge to contribute to the use of data analytics in business.

Details

Career Level: Postgraduate
Unit Level: Level 8
Credit Points: 6
Student Contribution Band: 10
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

Students enrolling in this unit must be undertaking the CL84 Master of Business Administration (International).

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Offerings For Semester 1 - 2021

Jakarta

Attendance Requirements

All on-campus students are expected to attend scheduled classes – in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Class and Assessment Overview

Recommended Student Time Commitment

Each 6-credit Postgraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.

Assessment Overview

1. Online Quiz(zes)
Weighting: 25%
2. Project (applied)
Weighting: 35%
3. Project (applied)
Weighting: 40%

Assessment Grading

This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University’s Grades and Results Policy for more details of interim results and final grades.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Identify the role of business analytics techniques in improving decision making for a data-driven organisation
  2. Analyse how specific business analytics techniques influence critical success factors
  3. Apply descriptive business analytics techniques to assist managers to solve business problems
  4. Apply predictive and prescriptive business analytics techniques to assist managers to solve business problems.
Alignment of Learning Outcomes, Assessment and Graduate Attributes
N/A Level
Introductory Level
Intermediate Level
Graduate Level
Professional Level
Advanced Level

Alignment of Assessment Tasks to Learning Outcomes

Assessment Tasks Learning Outcomes
1 2 3 4
1 - Online Quiz(zes) - 25%
2 - Project (applied) - 35%
3 - Project (applied) - 40%

Alignment of Graduate Attributes to Learning Outcomes

Graduate Attributes Learning Outcomes
1 2 3 4
1 - Knowledge
2 - Communication
3 - Cognitive, technical and creative skills
4 - Research
5 - Self-management
6 - Ethical and Professional Responsibility
7 - Leadership

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7
1 - Online Quiz(zes) - 25%
2 - Project (applied) - 35%
3 - Project (applied) - 40%
Textbooks and Resources

Textbooks

Prescribed

Business Analytics 4th Edition (2020)

Authors: Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann
Cengage Learning
Boston Boston , MA , US
ISBN: 9780357131787
Binding: Paperback

IT Resources

You will need access to the following IT resources:
  • CQUniversity Student Email
  • Internet
  • Unit Website (Moodle)
  • Excel spreadsheet software
Referencing Style

All submissions for this unit must use the referencing style: American Psychological Association 7th Edition (APA 7th edition)

For further information, see the Assessment Tasks.

Teaching Contacts
Sumartoyo Sumartoyo Unit Coordinator
s.sumartoyo@cqu.edu.au
Swee Kuik Unit Coordinator
s.kuik@cqu.edu.au
Schedule
Week 1 Begin Date: 12 Jul 2021

Module/Topic

Introduction to Business Analytics

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 2 Begin Date: 19 Jul 2021

Module/Topic

Descriptive Statistics

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 3 Begin Date: 26 Jul 2021

Module/Topic

Data Visualisation

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 4 Begin Date: 02 Aug 2021

Module/Topic

Probability and Modelling Uncertainty

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 5 Begin Date: 09 Aug 2021

Module/Topic

Regression Analysis

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Vacation Week Begin Date: 16 Aug 2021

Module/Topic

Chapter

Events and Submissions/Topic

Week 6 Begin Date: 23 Aug 2021

Module/Topic

Statistical Inference

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Professional Report: Case Study and Data Analytics Due: Week 6 Friday (27 Aug 2021) 11:00 pm AEST
Week 7 Begin Date: 30 Aug 2021

Module/Topic

Decision Analytics

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 8 Begin Date: 06 Sep 2021

Module/Topic

Optimisation Concept

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 9 Begin Date: 13 Sep 2021

Module/Topic

Spreadsheet Models

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 10 Begin Date: 20 Sep 2021

Module/Topic

Optimisation and Sensitivity Analysis

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 11 Begin Date: 27 Sep 2021

Module/Topic

Forecasting and Time Series

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Week 12 Begin Date: 04 Oct 2021

Module/Topic

Data Mining

Chapter

Lecture notes and materials are available in Moodle.

Events and Submissions/Topic

Professional Report: Analytical Modelling and Decision Making Due: Week 12 Friday (8 Oct 2021) 11:00 pm AEST
Review/Exam Week Begin Date: 11 Oct 2021

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 18 Oct 2021

Module/Topic

Chapter

Events and Submissions/Topic

Assessment Tasks

1 Online Quiz(zes)

Assessment Title
Online Quiz

Task Description

Assessment 1 comprises two main tasks:

Task A: Online Quiz (Weighted score: 10%) - The quiz includes 20 questions and has a time limit of 30 minutes. It is designed for students to understand key concepts and apply techniques and/or tools to analytically examine and/or propose solutions to business problems from the selected topics in this unit.

Task B: Online Quiz (Weighted score: 15%) - The quiz includes about 20-40 short and long questions and has a time limit of 60 minutes. It is designed for students to understand key concepts and apply techniques and/or tools to analytically examine and/or propose solutions to business problems from the selected topics in this unit.


Number of Quizzes

2


Frequency of Quizzes

Other


Assessment Due Date

The assessments will be due in Weeks 5 and 11. The exact due dates will be made available on the unit website.


Return Date to Students

Results will be made available on the unit website.


Weighting
25%

Assessment Criteria

No Assessment Criteria


Referencing Style

Submission
Online

Learning Outcomes Assessed
  • Identify the role of business analytics techniques in improving decision making for a data-driven organisation
  • Analyse how specific business analytics techniques influence critical success factors


Graduate Attributes
  • Knowledge
  • Ethical and Professional Responsibility

2 Project (applied)

Assessment Title
Professional Report: Case Study and Data Analytics

Task Description

The assessment is designed for students to apply fundamental data analytics tools and/or techniques. The assessment involves writing a 2000-words business report responding to assessment questions related to specific cases and the numerical data files that store information specific to the cases will be provided on the unit website. Submit your business report including excel spreadsheet and/or any relevant calculations, with a cover sheet showing the unit name and number, assessment number, your name and student number. You can discuss your assessment ideas in the unit Discussion Forum (Case Study), before you complete and submit the assessment.


Assessment Due Date

Week 6 Friday (27 Aug 2021) 11:00 pm AEST


Return Date to Students

Week 8 Monday (6 Sept 2021)

Grades and feedback comments are released in Moodle. Feedback Studio and the Grade book are the designated platforms for reviewing outcomes from the assessment process


Weighting
35%

Assessment Criteria

Your report analysis, recommendations and presentation will be assessed according to the following criteria.

  • Demonstrated understanding of data analytics with techniques and/or tools that are related to the questions posed: 25%
  • Accurately suggest and develop the model for detailed analysis in relation to the case studies: 25%
  • Able to articulate and evaluate case studies to provide managerial insights and practical limitations based on quantitative outcomes: 20%
  • Provide appropriate and well-structured, concise and clear expression of decision making arguments: 10%
  • Provide a clear flow of thought throughout the business report, evidenced by succinct Executive Summary, Introduction, and Conclusion: 10%
  • Adherence to APA Reference format: 5%
  • Clarity of written expression, grammar, spelling: 5%

Report length 2000-words. However, the summary, table of contents, reference list and appendices are excluded from a report’s word count.

Submissions must be in Professional Report format using Word with 1.5 line spacing and Times Roman 12-point font.

Late submissions will also be penalised at the rate of "five percent of the total marks available for the assessment each calendar day (full or part) it is overdue" (Policy: Assessment of Coursework section 3.2.4)


Referencing Style

Submission
Online

Learning Outcomes Assessed
  • Identify the role of business analytics techniques in improving decision making for a data-driven organisation
  • Apply descriptive business analytics techniques to assist managers to solve business problems
  • Apply predictive and prescriptive business analytics techniques to assist managers to solve business problems.


Graduate Attributes
  • Knowledge
  • Communication
  • Cognitive, technical and creative skills
  • Self-management

3 Project (applied)

Assessment Title
Professional Report: Analytical Modelling and Decision Making

Task Description

The assessment is designed for students to apply analytical techniques and/or methods for solving a real world application in your chosen area. The assessment involves writing a 2500-word business report responding to assessment questions related to specific topics and/or decision making analysis. Submit your 2500-word professional report including excel spreadsheet and/or any relevant calculations through Turnitin, Moodle, with a cover sheet showing unit name and number, assessment number, your name and student number. Assessment details and guideline will be provided on the unit website. You can discuss your assessment ideas in the unit Discussion Forum (Applied Project), before you complete and submit the assessment.


Assessment Due Date

Week 12 Friday (8 Oct 2021) 11:00 pm AEST


Return Date to Students

Return Date to Students Results and feedback will be made available on the unit website after Grade Certification.


Weighting
40%

Assessment Criteria

Your report analysis, recommendations and presentation will be assessed according to the following criteria.

  • Demonstrated understanding of analytical models that are related to the questions posed: 15%
  • Critical evaluation and integration of relevant academic and literature to provide theoretical and practical aspects. Insights from a minimum of 10 academic journal articles must be incorporated in your critical analysis: 15%
  • Accurately suggest and develop the model for detailed analysis in relation to the applications: 20%
  • Able to articulate and evaluate scenario modelling to provide managerial insights and practical limitations based on quantitative outcomes: 15%
  • Provide appropriate and well-structured, concise and clear expression of decision making arguments in terms of theoretical and practical elements 15%
  • Provide a clear flow of thought throughout the business report, evidenced by succinct Executive Summary, Introduction, and Conclusion: 10%
  • Adherence to APA Reference format: 5%
  • Clarity of written expression, grammar, spelling: 5%

Report length 2500-words. However, the summary, table of contents, reference list and appendices are excluded from a report’s word count.

Submissions must be in Business Report format using Word with 1.5 line spacing and Times Roman 12-point font.

Late submissions will also be penalised at the rate of "five percent of the total marks available for the assessment each calendar day (full or part) it is overdue" (Policy: Assessment of Coursework section 3.2.4)


Referencing Style

Submission

No submission method provided.


Learning Outcomes Assessed
  • Analyse how specific business analytics techniques influence critical success factors
  • Apply descriptive business analytics techniques to assist managers to solve business problems
  • Apply predictive and prescriptive business analytics techniques to assist managers to solve business problems.


Graduate Attributes
  • Knowledge
  • Communication
  • Cognitive, technical and creative skills
  • Self-management

Academic Integrity Statement

As a CQUniversity student you are expected to act honestly in all aspects of your academic work.

Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.

When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.

Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.

As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.

What is a breach of academic integrity?

A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.

Why is academic integrity important?

A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.

Where can I get assistance?

For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.

What can you do to act with integrity?