CQUniversity Unit Profile
COIS13013 Business Intelligence
Business Intelligence
All details in this unit profile for COIS13013 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
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

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

Career Level: Undergraduate
Unit Level: Level 3
Credit Points: 6
Student Contribution Band: 8
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

Pre-requisites: (COIT12203 Workflow Analysis & Management and COIT11240 Dashboard Design and Visualisation) OR (COIT12203 Workflow Analysis & Management 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 - 2021

Brisbane
Melbourne
Online
Rockhampton
Sydney

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 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

Bundaberg, Cairns, Emerald, Gladstone, Mackay, Rockhampton, Townsville
Adelaide, Brisbane, Melbourne, Perth, Sydney

Assessment Overview

1. Written Assessment
Weighting: 30%
2. Written Assessment
Weighting: 40%
3. Group Work
Weighting: 30%

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.

Previous Student Feedback

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 Student and staff feedback

Feedback

The final assessment has more work but less marks allocated.

Recommendation

Review the assessment requirements to ensure the tasks to be completed equates to the allocated weighting.

Feedback from Unit evaluation feedback

Feedback

The presentation task requirements can be more clear.

Recommendation

Review the presentation task requirements and provide more instructions for this task.

Feedback from Student and staff feedback

Feedback

Workshops in weeks 11 and 12 are helpful for building the understandings of Business Intelligence, especially in the last week, when the whole teaching team joined the workshop to share their business analysis and intelligence experiences.

Recommendation

Continue to run the workshops in the last two weeks and prepare some novel topics of BI for discussion and demonstration in workshops.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Apply the principles of decision theory to interpret the needs of decision-makers
  2. Analyse the needs of computerised support for managerial decision making and business performance reporting
  3. Evaluate the roles, trends and impacts of various business intelligence and analytics tools in organisations
  4. Analyse the technological architecture required for building business intelligence systems in organisations
  5. Evaluate the importance of data analysis, data processing and visualisation
  6. 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 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 5 6
1 - Written Assessment - 30%
2 - Written Assessment - 40%
3 - Group Work - 30%

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

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8 9
1 - Written Assessment - 30%
2 - Written Assessment - 40%
3 - Group Work - 30%
Textbooks and Resources

Textbooks

Prescribed

Business Intelligence and Analytics: Systems for Decision Support, Global 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

IT Resources

You will need access to the following 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)
Referencing Style

All submissions for this unit must use the referencing style: Harvard (author-date)

For further information, see the Assessment Tasks.

Teaching Contacts
Yufeng Lin Unit Coordinator
y.lin@cqu.edu.au
Schedule
Week 1 Begin Date: 08 Mar 2021

Module/Topic

Overview of Business Analytics and Intelligence

Chapter

Chapter 1

Events and Submissions/Topic

Week 2 Begin Date: 15 Mar 2021

Module/Topic

Foundations and Technologies for Decision Making

Chapter

Chapter 2 

Events and Submissions/Topic

Week 3 Begin Date: 22 Mar 2021

Module/Topic

Data Warehousing for Business Intelligence

Chapter

Chapter 3 

Events and Submissions/Topic

Week 4 Begin Date: 29 Mar 2021

Module/Topic

Business Reporting, Visual Analytics, and Performance Management

Chapter

Chapter 4 

Events and Submissions/Topic

Week 5 Begin Date: 05 Apr 2021

Module/Topic

Predictive Analytics with Data Mining

Chapter

Chapter 5

Events and Submissions/Topic

Vacation Week Begin Date: 12 Apr 2021

Module/Topic

Chapter

Events and Submissions/Topic

Week 6 Begin Date: 19 Apr 2021

Module/Topic

Integration and Analysis of Unstructured Data

Chapter

Chapter 7 & 8

Events and Submissions/Topic

Assignment 1: Decision Making, Visual Analytics and Case Study Due: Week 6 Monday (19 Apr 2021) 11:45 pm AEST
Week 7 Begin Date: 26 Apr 2021

Module/Topic

Modelling and Analysis: Methods and Simulation

Chapter

Chapter 10

Events and Submissions/Topic

Week 8 Begin Date: 03 May 2021

Module/Topic

Data Visualisation and Dashboard Design

Chapter

(Materials will be provided)

Events and Submissions/Topic

Week 9 Begin Date: 10 May 2021

Module/Topic

Automated Decision Support Systems and Expert Systems

Chapter

Chapter 11

Events and Submissions/Topic

Week 10 Begin Date: 17 May 2021

Module/Topic

Business Analytics and Intelligent: Emerging Trends and Future Impacts

Chapter

Chapter 14

Events and Submissions/Topic

Week 11 Begin Date: 24 May 2021

Module/Topic

Workshop 1: Business Analytics Case Study

Chapter

(Materials will be provided)

Events and Submissions/Topic

Assignment 2: Modeling, Data Mining and Dashboard Design Due: Week 11 Friday (28 May 2021) 11:45 pm AEST
Week 12 Begin Date: 31 May 2021

Module/Topic

Workshop 2: Business Intelligence Application Scenarios

Chapter

(Materials will be provided)

Events and Submissions/Topic

Review/Exam Week Begin Date: 07 Jun 2021

Module/Topic

Chapter

Events and Submissions/Topic

Assignment 3: Groupwork on Business Intelligence Development and Implementation Due: Review/Exam Week Friday (11 June 2021) 11:45 pm AEST
Exam Week Begin Date: 14 Jun 2021

Module/Topic

Chapter

Events and Submissions/Topic

Term Specific Information

For any queries, please contact the unit coordinator: Dr Yufeng Lin (e-mail: y.lin@cqu.edu.au).

Assessment Tasks

1 Written Assessment

Assessment Title
Assignment 1: Decision Making, Visual Analytics and Case Study

Task Description

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 unit website.


Assessment Due Date

Week 6 Monday (19 Apr 2021) 11:45 pm AEST

Late submissions are subject to the university's late submission penalty policies.


Return Date to Students

Week 8 Monday (3 May 2021)

Assessments will be returned through Moodle website. Late submissions with or without extension approvals will be returned after the above date.


Weighting
30%

Assessment Criteria

Your assessment will be marked according to the following aspects:

  • Appropriate use of Visual DSS for generating models and deriving business solutions
  • Data visualisation and visual analytics
  • Discussion on business intelligence projects' development and implementation

You will be assessed on your responses regarding accuracy, clarity, and suitability for the given contexts. See the unit website for more details.


Referencing Style

Submission
Online

Submission Instructions
This assignment should be attempted and submitted individually.

Learning Outcomes Assessed
  • 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


Graduate Attributes
  • Communication
  • Problem Solving
  • Critical Thinking
  • Information Literacy
  • Team Work
  • Information Technology Competence

2 Written Assessment

Assessment Title
Assignment 2: Modeling, Data Mining and Dashboard Design

Task Description

There are three parts in Assignment 2:

  • The first part is related to data processing, modelling and analysis, and automated decision support system. Students are required to do some problem-solving calculations, data preparation, modelling and analysis for building an automatic decision support 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, analyses, and displays key performance indicators (KPI), metrics and so forth 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 unit website.


Assessment Due Date

Week 11 Friday (28 May 2021) 11:45 pm AEST

Late submissions are subject to the university's late submission penalty policies.


Return Date to Students

Review/Exam Week Friday (11 June 2021)

Assessments will be returned through Moodle. Late submissions with or without extension approvals may be returned after the above date.


Weighting
40%

Assessment Criteria

Your second assignment will be marked according to the following aspects:

  • Data processing, model and analysis, automated decision support system discussion
  • Appropriate use of data mining tool for data analysis
  • A case study on information visualisation and analysis

You will be assessed on your responses regarding accuracy, clarity, and suitability for the given contexts. See the unit website for more details.


Referencing Style

Submission
Online

Submission Instructions
This assignment should be attempted and submitted individually.

Learning Outcomes Assessed
  • 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.


Graduate Attributes
  • Communication
  • Problem Solving
  • Critical Thinking
  • Information Literacy
  • Team Work
  • Information Technology Competence
  • Ethical practice

3 Group Work

Assessment Title
Assignment 3: Groupwork on Business Intelligence Development and Implementation

Task Description

In this group assignment (the group size is to be three, although variations may need to be made by the tutor depending on the class size), your group is required to draft 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 BI application area. The report will demonstrate a framework of business analytics and intelligence in a specific business intelligence application area. A presentation will be required to show your understanding of BI or the specific technologies used to build BI applications.


Assessment Due Date

Review/Exam Week Friday (11 June 2021) 11:45 pm AEST

Late submissions are subject to the university's late submission penalty policies.


Return Date to Students

Assessments will be returned on the Certification date (required for the unit without an exam).


Weighting
30%

Assessment Criteria

Your third assignment will be marked according to the following aspects:

  • Introduction of the chosen BI application scenario 
  • The business analytics framework 
  • How to apply artificial intelligence to the business analytics model 
  • Presentation slides 
  • Presentation (a recorded video provided by each online group) 

Your group will be assessed on the responses regarding teamwork, accuracy, clarity, and suitability for a chosen BI application. See the unit website for more details.


Referencing Style

Submission
Online Group

Submission Instructions
This assignment should be attempted as a teamwork and only one of you are requested to submit the assignment for your group.

Learning Outcomes Assessed
  • 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.


Graduate Attributes
  • Communication
  • Problem Solving
  • Critical Thinking
  • Information Literacy
  • Team Work
  • Information Technology Competence
  • Ethical practice

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?