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
Pre-requisites or Co-requisites
Prerequisite: STAT20029 Statistics for Managerial Decisions
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 Term 1 - 2020
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).
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.
Class Timetable
Assessment Overview
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.
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Monitoring Academic Progress (MAP) Policy and Procedure – Domestic Students
- Monitoring Academic Progress (MAP) Policy and Procedure – International Students
- Student Refund and Credit Balance Policy and Procedure
- Student Feedback – Compliments and Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
- 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
- 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.
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 | ||||
| 8 - Aboriginal and Torres Strait Islander Cultures | ||||
Alignment of Assessment Tasks to Graduate Attributes
| Assessment Tasks | Graduate Attributes | |||||||
|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
| 1 - Online Quiz(zes) - 25% | ||||||||
| 2 - Project (applied) - 35% | ||||||||
| 3 - Project (applied) - 40% | ||||||||
Textbooks
Business Analytics
Edition: 3 (2019)
Authors: Camm, Cochran, Fry, Ohlmann, Anderson, Sweeney, Williams
Cengage Learning
Boston Boston , MA , United States
ISBN: 9781337406420
Binding: eBook
Additional Textbook Information
The eBook is available at the Cengage website here:
https://cengage.com.au/product/title/business-analytics/isbn/9781337406420
However, paper copies can still be purchased from the CQUni Bookshop here: http://bookshop.cqu.edu.au
IT Resources
- CQUniversity Student Email
- Internet
- Unit Website (Moodle)
- MS Excel Solver Add-in (MS office)
- MS Excel
- MS Access 2007 or 2010 or later
All submissions for this unit must use the referencing style: American Psychological Association 6th Edition (APA 6th edition)
For further information, see the Assessment Tasks.
p.best@cqu.edu.au
Module/Topic
Introduction to unit
Introduction to business analytics
Analytics in banking
Analytics in other areas
Competing with analytics
Chapter
Cam 3e 1, App A
Events and Submissions/Topic
Module/Topic
Chapter
Cam 3e App B, B.1-2
Events and Submissions/Topic
Module/Topic
Exporting data, importing data, dimensional modelling
Chapter
Cam 3e App B, B.3-5
Events and Submissions/Topic
Quiz 1 opens on Friday 27 March, 9:00 AEST.
Module/Topic
Descriptive statistics
Chapter
Cam 3e 2
Events and Submissions/Topic
Quiz 1 closes on Friday 3 April 9:00 AEST.
Module/Topic
Data visualization
Chapter
Cam 3e 3
Events and Submissions/Topic
Quiz 2 opens on Friday 10 April 9:00 AEST.
Module/Topic
Self-study
Chapter
Events and Submissions/Topic
Module/Topic
Descriptive data mining
Missing data
Cluster
Association/sequence
Chapter
Cam 3e 4
Events and Submissions/Topic
Quiz 2 closes on Friday 24 April 9:00 AEST.
Module/Topic
Regression
Chapter
Cam 3e 7
Events and Submissions/Topic
Quiz 3 opens on Friday 1 May 9:00 AEST.
Module/Topic
Time series analysis and Forecasting
Chapter
Cam 3e 8
Events and Submissions/Topic
Quiz 3 closes on Friday 8 May 9:00 AEST.
Project 1 - Descriptive Techniques Due: Week 8 Friday (8 May 2020) 5:00 pm AEST
Module/Topic
Simulation
Chapter
Cam 3e 11
Events and Submissions/Topic
Quiz 4 opens on Friday 15 May 9:00 AEST.
Module/Topic
Linear optimization
Chapter
Cam 3e 12
Events and Submissions/Topic
Quiz 4 closes on Friday 22 May 9:00 AEST.
Module/Topic
Data analytics, maturity, institutionalization, agility, performance
Chapter
Readings
Events and Submissions/Topic
Quiz 5 opens on Friday 29 May 9:00 AEST.
Module/Topic
Unit Review
Chapter
Events and Submissions/Topic
Quiz 5 closes on 5 June 9:00 AEST.
Project 2 - Predictive and Prescriptive Techiques Due: Week 12 Friday (5 June 2020) 5:00 pm AEST
Module/Topic
Self-study
Chapter
Events and Submissions/Topic
Module/Topic
Chapter
Events and Submissions/Topic
1 Online Quiz(zes)
Five (5) fortnightly online quizzes are required to be completed. Each quiz is to be completed individually, is open for approximately 7 days, and covers the preceding 2 weeks of classes. The first quiz opens in Week 3. Each quiz consists of a set of multiple-choice questions and is marked out of 15. The weighting for quiz results is 25% of the total marks.
5
Fortnightly
Fortnightly quizzes will open on Friday at 9:00 AEST and will close on the following Friday at 9:00 AEST. Quiz 1 opens on Friday in Week 2 and closes on Friday in Week 3. Quiz 2 opens on Friday in Week 4 and closes on Friday in Week 5. And, so on.
Your results of the quiz will be automatically generated and will be displayed upon completion of the quiz. You can access your results again on the unit website via the Gradebook. You willl be able to check your quiz for incorrect answers after the quiz has closed.
Assessing students' ability to distinguish the primary categories of business analytics
techniques, and identify their role in improving decision making and critical success
factors for a data-driven organisation.
- 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
- Knowledge
- Ethical and Professional Responsibility
2 Project (applied)
This project assesses students' ability to apply descriptive business analytics techniques to assist managers to solve business problems. Several case studies will be examined, where students will use software to analyse data and provide a report to management on findings.
Week 8 Friday (8 May 2020) 5:00 pm AEST
Submit Project 1 through Moodle.
Marks and feedback will be available within 2 weeks of the due date.
The project will examine students' ability in identifying relevant techniques and demonstrating knowledge, applying relevant techniques and knowledge to solve problems, and quality of writing, grammar, syntax and spelling.
- 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.
- Knowledge
- Communication
- Cognitive, technical and creative skills
- Self-management
3 Project (applied)
This project assesses students' ability to apply predictive and prescriptive business analytics techniques to assist managers to solve business problems. Several case studies will be examined, where students will use software to analyse data and provide a report to management on findings.
Week 12 Friday (5 June 2020) 5:00 pm AEST
Submit Project 2 through Moodle.
Marks and feedback will be available within 2 weeks of the due date.
The project will examine students' ability in identifying relevant techniques and demonstrating knowledge, applying relevant techniques and knowledge to solve problems, and quality of writing, grammar, syntax and spelling.
- 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.
- Knowledge
- Communication
- Cognitive, technical and creative skills
- Self-management
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?
