Overview
The application of business intelligence and analytics have transformed the way in which organisations operate. Through the use of business intelligence and analytics tools, organisations are able to better understand how their businesses are performing, make well-informed decisions that improve business performance and create new strategic opportunities for growth. This unit equips you with the knowledge of various business intelligence concepts, tools and analytical techniques that organisations use for improving their decision making and to achieve competitive advantage. You will learn about the role of various information systems (Management Support Systems, Decision Support Systems, Knowledge-Based Systems, Group Support Systems) and how they are integrated at the enterprise level to support decision making. In this unit, you will specifically learn about data mining, data visualisation, text and web analytics and use a data mining tool to classify and analyse data.
Details
Pre-requisites or Co-requisites
Pre-requisites: COIT11226 Systems Analysis and COIT11240 Dashboard Design and Visualisation OR COIT11226 Systems Analysis and HRMT11010 Organisational Behaviour.
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 Undergraduate 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.
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Feedback from Unit evaluation
Power BI is a useful tool for business analytics service, which provides interactive visualisations and business intelligence capabilities. More practicals on how to use Power BI can be provided for this unit.
Some related practicals of Power BI can be designed as tutorial activities to enhance students' understanding of business analytics.
Feedback from Staff feedback
The presentation assessment task for online students should be redesigned with specific assessment methods, and for the on-campus students, it can be made as group-based.
Review and update the presentation assessment tasks to suit both on-campus and distance students.
- Apply the principles of decision theory to interpret the needs of decision makers
- Analyse the needs of computerised support for managerial decision making and business performance reporting
- Evaluate the roles, trends and impacts of various business intelligence and analytics tools in organisations
- Analyse the technological architecture required for building business intelligence systems in organisations
- Evaluate the importance of data analysis, data processing and visualisation
- Apply business intelligence and analytics software tools to solve real world problems and interpret results.
Australian Computer Society (ACS) recognises the Skills Framework for the Information Age (SFIA). SFIA is in use in over 100 countries and provides a widely used and consistent definition of ICT skills. SFIA is increasingly being used when developing job descriptions and role profiles.
ACS members can use the tool MySFIA to build a skills profile at https://www.acs.org.au/professionalrecognition/mysfia-b2c.html
This unit contributes to the following workplace skills as defined by SFIA. The SFIA code is included:
- Analytics (INAN)
- Business Analysis (BUAN)
- Data Analysis (DTAN)
- Data Visualisation (VISL)
Alignment of Assessment Tasks to Learning Outcomes
Assessment Tasks | Learning Outcomes | |||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | |
1 - Written Assessment - 40% | ||||||
2 - Written Assessment - 40% | ||||||
3 - Group Work - 20% |
Alignment of Graduate Attributes to Learning Outcomes
Graduate Attributes | Learning Outcomes | |||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | |
1 - Communication | ||||||
2 - Problem Solving | ||||||
3 - Critical Thinking | ||||||
4 - Information Literacy | ||||||
5 - Team Work | ||||||
6 - Information Technology Competence | ||||||
7 - Cross Cultural Competence | ||||||
8 - Ethical practice | ||||||
9 - Social Innovation | ||||||
10 - 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 | 9 | 10 | |
1 - Written Assessment - 40% | ||||||||||
2 - Written Assessment - 40% | ||||||||||
3 - Group Work - 20% |
Textbooks
Business Intelligence and Analytics: Systems for Decision Support, Global Edition
Edition: 10th (2014)
Authors: Ramesh Sharda, Dursun Delen and Efraim Turban
Pearson
Upper Saddle River Upper Saddle River , New Jers , USA
ISBN: 9781292009209
Binding: Other
Additional Textbook Information
Copies can be purchased at the CQUni Bookshop here: http://bookshop.cqu.edu.au (search on the Unit code)
IT Resources
- CQUniversity Student Email
- Internet
- Unit Website (Moodle)
- WEKA (Version: 3.8.1 – 64 Bit)
- Trueblue Visual DSS (Release 6789 Student Edition – 32 Bit)
- Microsoft Power BI Desktop (Version: 2.53.4954.621 – 64 Bit)
- Microsoft Power BI publisher for Excel (Version: 2.37.3272.33601 – 32 Bit for Microsoft office -32 Bit; 64 Bit for Microsoft office -64 Bit)
- Python (Version 3.8.1) https://www.python.org/ (optional)
- Tableau Desktop (Version 2019.4.1) (optional)
- R (free, open-source data analysis software): http://cran.r-project.org/ (optional)
All submissions for this unit must use the referencing style: Harvard (author-date)
For further information, see the Assessment Tasks.
y.lin@cqu.edu.au
Module/Topic
Overview of Business Analytics and Intelligence
Chapter
Chapter 1
Events and Submissions/Topic
Module/Topic
Foundations and Technologies for Decision Making
Chapter
Chapter 2
Events and Submissions/Topic
Module/Topic
Data Warehousing for Business Intelligence
Chapter
Chapter 3
Events and Submissions/Topic
Module/Topic
Business Reporting, Visual Analytics, and Performance Management
Chapter
Chapter 4
Events and Submissions/Topic
Module/Topic
Predictive Analytics with Data Mining
Chapter
Chapter 5
Events and Submissions/Topic
Module/Topic
Chapter
Events and Submissions/Topic
Module/Topic
Integration and Analysis of Unstructured Data
Chapter
Chapter 7 & 8
Events and Submissions/Topic
Module/Topic
Modelling and Analysis: Methods and Simulation
Chapter
Chapter 10
Events and Submissions/Topic
Module/Topic
Data Visualisation and Dashboard Design
Chapter
(Materials will be provided)
Events and Submissions/Topic
Module/Topic
Automated Decision Systems and Expert Systems
Chapter
Chapter 11
Events and Submissions/Topic
Module/Topic
Business Analytics and Intelligent: Emerging Trends and Future Impacts
Chapter
Chapter 14
Events and Submissions/Topic
Module/Topic
Workshop 1: Business Analytics Case Study
Chapter
(Materials will be provided)
Events and Submissions/Topic
Module/Topic
Workshop 2: Business Intelligence Application Scenarios
Chapter
(Materials will be provided)
Events and Submissions/Topic
Module/Topic
Chapter
Events and Submissions/Topic
Module/Topic
Chapter
Events and Submissions/Topic
Unit Coordinator: Dr Yufeng Lin
Contect Number: 0747 265 329
Email: y.lin@cqu.edu.au
1 Written Assessment
There are three parts in Assignment 1:
- The first part is related to decision making for business investment. You are required to use a Visual DSS tool to generate models and derive solutions for making decisions on business investment.
- The second part is related to data and information visualisation. You are required to generate data visualisation by using Power BI to conduct business analytics.
- The third part is related to business intelligence case study. You are required to write a report from a given BI application scenario.
More details will be provided on the Moodle website.
Week 6 Monday (20 Apr 2020) 11:45 pm AEST
Week 8 Monday (4 May 2020)
Assessments will be returned through Moodle website. Late submissions with or without extension approvals will be returned after the above date.
Your assessment will be marked according to the following criteria:
Appropriate use of Visual DSS for generating models and deriving business solutions | 20 marks |
Data visualisation and visual analytics | 10 marks |
Discussion on business intelligence projects' development and implementation | 10 marks |
- Apply the principles of decision theory to interpret the needs of decision makers
- Analyse the needs of computerised support for managerial decision making and business performance reporting
- Analyse the technological architecture required for building business intelligence systems in organisations
- Evaluate the importance of data analysis, data processing and visualisation
- Communication
- Problem Solving
- Critical Thinking
- Information Literacy
- Team Work
- Information Technology Competence
2 Written Assessment
There are three parts in Assignment 2:
- The first part is related to data processing, modelling and analysis, and automated decision system. Students are required to do some problem-solving calculations, data preparation, modelling and analysis for building an automatic decision system.
- The second part is related to data mining. Students are required to use a specific data mining tool to generate a classification tree and provide a summary of the classification result.
- The third part is related to descriptive analytics information management tool (Dashboard) that visually tracks, analyse and display key performance indicators (KPI), metrics etc. to monitor the overall business performance. Students are required to design/discuss a business intelligence dashboard to facilitate decision making.
More details will be provided on the Moodle website.
Week 10 Friday (22 May 2020) 11:45 pm AEST
Week 12 Friday (5 June 2020)
Your second assignment will be marked according to the following criteria:
Data processing, model and analysis, automated decision system discussion | 15 marks |
Appropriate use of data mining tool for data analysis | 15 marks |
A case study on information visualisation and analysis | 10 marks |
- Apply the principles of decision theory to interpret the needs of decision makers
- Analyse the needs of computerised support for managerial decision making and business performance reporting
- Evaluate the roles, trends and impacts of various business intelligence and analytics tools in organisations
- Apply business intelligence and analytics software tools to solve real world problems and interpret results.
- Communication
- Problem Solving
- Critical Thinking
- Information Literacy
- Team Work
- Information Technology Competence
- Ethical practice
3 Group Work
In this group assessment (the group size is to be 3, although variations may need to be made by the tutor depending on the class size), you are required to write a report which describes the achievement of data analysis modelling on a specific business project with the application of business intelligence. The case study or scenario can be from any application area. The report is to demonstrate the application of business analytics and intelligence in a specific business intelligence application area and presentation will be required to show your understandings of BI or the specific technologies used to build BI applications.
Review/Exam Week Friday (12 June 2020) 11:45 pm AEST
Assessments will be returned on the Certificate date (required for the unit without an exam)
Your third assignment will be marked according to the following criteria:
Introduction of the chosen BI application scenario | 3 marks |
The business analytics framework | 3 marks |
How to apply artificial intelligence to the business analytics model | 4 marks |
Presentation slides | 4 marks |
Presentation (Recorded videos provided by online groups) | 6 marks |
- Evaluate the roles, trends and impacts of various business intelligence and analytics tools in organisations
- Analyse the technological architecture required for building business intelligence systems in organisations
- Evaluate the importance of data analysis, data processing and visualisation
- Apply business intelligence and analytics software tools to solve real world problems and interpret results.
- Communication
- Problem Solving
- Critical Thinking
- Information Literacy
- Team Work
- Information Technology Competence
- Ethical practice
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.