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 unit reviews how managers use computerised decision support systems for accessing important information, the principles of decision making, modelling and how Business Intelligence tools are used by enterprises to support decision making. The unit develops an understanding of what is unique about Information Systems that provide support for decision makers and how various information systems (DSS, Knowledge Based Systems, Group Support Systems, Business Intelligence) are integrated at the enterprise level to support decision making. Students complete practical work using a financial modelling language, analyse the information needs of decision makers, evaluate and develop tools in the implementation of what we call, all these technologies and systems collectively, Management Support Systems (MSS).

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-requisite: COIT11226

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 - 2018

Brisbane
Distance
Melbourne
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: 40%
2. Presentation and Written Assessment
Weighting: 60%

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 Unit evaluation

Feedback

There should be a group activity in the unit.

Recommendation

Group activities on DSS software application will be included in tutorial classes.

Feedback from Unit evaluation

Feedback

Individual presentation assessment should be made a group based assessment.

Recommendation

The description of the presentation assessment will be rewritten. Students will be given the choice to present either in groups or individually.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. describe the principles of decision theory and apply the theory to interpret the needs of decision makers, and apply the results in the implementation of MSS
  2. describe basic concepts of MSS modelling and apply the process of model formulation and solution
  3. analyse the information needs of decision makers and apply the results to business performance reporting
  4. evaluate the role of Business Intelligence and Decision Support Systems tools in organisations at the enterprise level
  5. describe role of knowledge in organisations and evaluate the use of collaborative technology to create, gather, and share knowledge
  6. conduct research into new areas and products, relate them to development of MSS, and present your results to others.

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:

  • Information Analysis (INAN)
  • Data Analysis (DTAN)
  • Research (RSCH)

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 - 40%
2 - Presentation and Written Assessment - 60%

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 - 40%
2 - Presentation and Written Assessment - 60%
Textbooks and Resources

Textbooks

Prescribed

Business Intelligence and Analytics: Systems for Decision Support 10th edn Global (2015)

Authors: Sharda, R., Delen, D., & Turban, E.
Upper Saddle River
NJ NJ , USA
ISBN: 9781292009209
Binding: Other

Additional Textbook Information


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)
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: 05 Mar 2018

Module/Topic

An Overview of Business Intelligence and Analytics

Chapter

Chapter 1

Events and Submissions/Topic

Week 2 Begin Date: 12 Mar 2018

Module/Topic

Foundations and Technologies for Decision Making

Chapter

Chapter 2 

Events and Submissions/Topic

Week 3 Begin Date: 19 Mar 2018

Module/Topic

Data Warehousing

Chapter

Chapter 3 

Events and Submissions/Topic

Week 4 Begin Date: 26 Mar 2018

Module/Topic

Business Reporting, Visual Analytics, and Business Performance Management

Chapter

Chapter 4 

Events and Submissions/Topic

Week 5 Begin Date: 02 Apr 2018

Module/Topic

Data Mining for Business Intelligence

Chapter

Chapter 5

Events and Submissions/Topic

Vacation Week Begin Date: 09 Apr 2018

Module/Topic

Chapter

Events and Submissions/Topic

Week 6 Begin Date: 16 Apr 2018

Module/Topic

Text Analytics, Text Mining, and Sentiment Analysis

Chapter

Chapter 7

Events and Submissions/Topic

Assignment 1 due Friday (20-Apr-2018) 11:45 pm AEST.


Assignment 1 - Decision Making and Virtual Analytics Due: Week 6 Friday (20 Apr 2018) 11:45 pm AEST
Week 7 Begin Date: 23 Apr 2018

Module/Topic

Web Analytics, Web Mining, and Social Analytics

Chapter

Chapter 8 

Events and Submissions/Topic

Week 8 Begin Date: 30 Apr 2018

Module/Topic

Modelling and Analysis: Heuristic Search Methods and Simulation

Chapter

Chapter 10 

Events and Submissions/Topic

Week 9 Begin Date: 07 May 2018

Module/Topic

Automated Decision Systems and Expert Systems

Chapter

Chapter 11 

Events and Submissions/Topic

Week 10 Begin Date: 14 May 2018

Module/Topic

Knowledge Management and Collaborative Systems

Chapter

Chapter 12 

Events and Submissions/Topic

Week 11 Begin Date: 21 May 2018

Module/Topic

Big Data and Analytics

Chapter

Chapter 13 

Events and Submissions/Topic

Week 12 Begin Date: 28 May 2018

Module/Topic

Business Analytics: Emerging Trends and Future Impacts

Chapter

Chapter 14 

Events and Submissions/Topic

Assignment 2 due Friday (01-Jun-2018) 11:45 pm AEST.


Assignment 2 - Business Intelligence and Analytics Due: Week 12 Friday (1 June 2018) 11:45 pm AEST
Review/Exam Week Begin Date: 04 Jun 2018

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 11 Jun 2018

Module/Topic

Chapter

Events and Submissions/Topic

Assessment Tasks

1 Written Assessment

Assessment Title
Assignment 1 - Decision Making and Virtual Analytics

Task Description

There are three parts to Assignment 1:

  • The first part is related to decision making on business investment. Students need 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 virtualization. Students are required to generate data virtualization by using Power BI to conduct business analytics.
  • The third part is related to business intelligence projects' development and implementation. Students are required to write a report from a given case study.

More details about Assignment 1 are available on the Moodle website.


Assessment Due Date

Week 6 Friday (20 Apr 2018) 11:45 pm AEST


Return Date to Students

Week 8 Friday (4 May 2018)

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


Weighting
40%

Assessment Criteria

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 virtualization and virtual analytics 10 marks
Discussion on business intelligence projects' development and implementation 10 marks


Referencing Style

Submission
Online

Submission Instructions
Your assignment must be submitted in doc/docx format. See the assignment specification on the Moodle website for details. .

Learning Outcomes Assessed
  • describe the principles of decision theory and apply the theory to interpret the needs of decision makers, and apply the results in the implementation of MSS
  • describe basic concepts of MSS modelling and apply the process of model formulation and solution
  • analyse the information needs of decision makers and apply the results to business performance reporting
  • evaluate the role of Business Intelligence and Decision Support Systems tools in organisations at the enterprise level
  • describe role of knowledge in organisations and evaluate the use of collaborative technology to create, gather, and share knowledge
  • conduct research into new areas and products, relate them to development of MSS, and present your results to others.


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

2 Presentation and Written Assessment

Assessment Title
Assignment 2 - Business Intelligence and Analytics

Task Description

Assignment 2 contains two parts: Part A, a written assignment with four questions including an oral presentation worth 45 marks, and Part B, an online quiz worth 15 marks.

The theoretical questions cover topics in business intelligence and analytics areas. Students are required to use a data mining tool to classify and analyse data. Internal students need to deliver an oral presentation to the class. External/distance students will be provided details regarding the oral presentation via email.

The online quiz consists of 30 True/False and Multiple-Choice questions. You will be given one attempt to complete the quiz. There will be a time limit of 45 minutes to complete the quiz.

More details about Assignment 2 are available on the Moodle website.


Assessment Due Date

Week 12 Friday (1 June 2018) 11:45 pm AEST


Return Date to Students

Assessments will be returned on the Certificate date (required for courses without exams)


Weighting
60%

Assessment Criteria

Your second assignment will be marked according to the following criteria.

Discussion on the importance of business intelligence 10 marks
Appropriate use of WEKA for data analysis 15 marks
A case study on Information Virtualizaiton and Analitics  10 marks
Oral presentation 10 marks
Online quiz 15 marks


Referencing Style

Submission
Online

Submission Instructions
Please check assignment 2 details on the Moodle course website.

Learning Outcomes Assessed
  • describe the principles of decision theory and apply the theory to interpret the needs of decision makers, and apply the results in the implementation of MSS
  • describe basic concepts of MSS modelling and apply the process of model formulation and solution
  • analyse the information needs of decision makers and apply the results to business performance reporting
  • evaluate the role of Business Intelligence and Decision Support Systems tools in organisations at the enterprise level
  • describe role of knowledge in organisations and evaluate the use of collaborative technology to create, gather, and share knowledge
  • conduct research into new areas and products, relate them to development of MSS, and present your results to others.


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?