CQUniversity Unit Profile
COIS13013 Business Intelligence
Business Intelligence
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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

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 virtualisation, 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-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 - 2019

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: 40%
2. Presentation and Written Assessment
Weighting: 45%
3. Online Quiz(zes)
Weighting: 15%

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 Students

Feedback

Tutorial videos on how to install and use the software Weka should be provided.

Recommendation

Add tutorial videos to guide students on how to install the software Weka and provide some examples of how to use Weka.

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)

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 - Online Quiz(zes) - 15%
2 - Written Assessment - 40%
3 - Presentation and Written Assessment - 45%

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 - Online Quiz(zes) - 15%
2 - Written Assessment - 40%
3 - Presentation and Written Assessment - 45%
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

Additional Textbook Information

Paper copies can be purchased at the CQUni Bookshop here: http://bookshop.cqu.edu.au (search on the Unit code)

However, ebook copies can purchased from the supplier here: http://www.pearson.com.au/9781292009261 

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: 11 Mar 2019

Module/Topic

An Overview of Business Intelligence and Analytics

Chapter

Chapter 1

Events and Submissions/Topic

Week 2 Begin Date: 18 Mar 2019

Module/Topic

Foundations and Technologies for Decision Making

Chapter

Chapter 2 

Events and Submissions/Topic

Week 3 Begin Date: 25 Mar 2019

Module/Topic

Data Warehousing

Chapter

Chapter 3 

Events and Submissions/Topic

Week 4 Begin Date: 01 Apr 2019

Module/Topic

Business Reporting, Visual Analytics, and Business Performance Management

Chapter

Chapter 4 

Events and Submissions/Topic

Week 5 Begin Date: 08 Apr 2019

Module/Topic

Data Mining for Business Intelligence

Chapter

Chapter 5

Events and Submissions/Topic

Vacation Week Begin Date: 15 Apr 2019

Module/Topic

Chapter

Events and Submissions/Topic

Week 6 Begin Date: 22 Apr 2019

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 (26 Apr 2019) 11:45 pm AEST
Week 7 Begin Date: 29 Apr 2019

Module/Topic

Web Analytics, Web Mining, and Social Analytics

Chapter

Chapter 8 

Events and Submissions/Topic

Week 8 Begin Date: 06 May 2019

Module/Topic

Modelling and Analysis: Heuristic Search Methods and Simulation

Chapter

Chapter 10 

Events and Submissions/Topic

Week 9 Begin Date: 13 May 2019

Module/Topic

Automated Decision Systems and Expert Systems

Chapter

Chapter 11 

Events and Submissions/Topic

Week 10 Begin Date: 20 May 2019

Module/Topic

Knowledge Management and Collaborative Systems

Chapter

Chapter 12 

Events and Submissions/Topic

Week 11 Begin Date: 27 May 2019

Module/Topic

Big Data and Analytics

Chapter

Chapter 13 

Events and Submissions/Topic

Week 12 Begin Date: 03 Jun 2019

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 (7 June 2019) 11:45 pm AEST
Review/Exam Week Begin Date: 10 Jun 2019

Module/Topic

Chapter

Events and Submissions/Topic

ASSIGNMENT 3 - ONLINE QUIZ Due: Review/Exam Week Monday (10 June 2019) 2:00 pm AEST
Exam Week Begin Date: 17 Jun 2019

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 in Assignment 1:

  • The first part is related to decision making on 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 virtualization. You 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. You are required to write a report from a given case study.

More details will be provided on the Moodle website.


Assessment Due Date

Week 6 Friday (26 Apr 2019) 11:45 pm AEST


Return Date to Students

Week 8 Friday (10 May 2019)

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 more details. .

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
  • 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

2 Presentation and Written Assessment

Assessment Title
ASSIGNMENT 2 - BUSINESS INTELLIGENCE AND ANALYTICS

Task Description

Assignment 2 contains a written assignment with four questions including an oral presentation.

The theoretical questions cover topics in business intelligence and analytics areas. You 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 allowed to provide a recorded video of the required oral presentation.


Assessment Due Date

Week 12 Friday (7 June 2019) 11:45 pm AEST


Return Date to Students

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


Weighting
45%

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


Referencing Style

Submission
Online

Submission Instructions
Please check more details on the Moodle website.

Learning Outcomes Assessed
  • 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.


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

3 Online Quiz(zes)

Assessment Title
ASSIGNMENT 3 - ONLINE QUIZ

Task Description

The quiz consists of a series of 30 True/False and Multiple Choice questions. Questions will be randomly selected from a pool of questions on topics in weeks 1 to 12. You are unlikely to be asked the same questions as other students, nor the same questions in subsequent attempts at the quiz. The time limit for each attempt is 45 minutes. The quiz automatically closes. If you have not submitted an attempt at the quiz by the due date, you will get no mark. Quizzes cannot be attempted and submitted after the due date.

You are allowed to attempt the quiz as many times as you want before the due date; however, the result of your last submission will be your final mark of the quiz.


Number of Quizzes


Frequency of Quizzes


Assessment Due Date

Review/Exam Week Monday (10 June 2019) 2:00 pm AEST


Return Date to Students

Review/Exam Week Monday (10 June 2019)

Immediately after the quiz closes.


Weighting
15%

Assessment Criteria

The quiz is automatically graded by the system based on the selection of correct or incorrect answers. Each attempt will be marked after you submit your answers. The result of your last submission will be your final mark of the quiz. Extensions are not possible for quizzes. If you miss the quiz, you cannot do it later.


Referencing Style

Submission
Online

Learning Outcomes Assessed
  • Apply the principles of decision theory to interpret the needs of decision makers
  • Evaluate the roles, trends and impacts of various business intelligence and analytics tools in organisations
  • Evaluate the importance of data analysis, data processing and visualisation


Graduate Attributes
  • Problem Solving
  • Critical Thinking

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?