COIS13013 - Business Intelligence

General Information

Unit Synopsis

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

Level Undergraduate
Unit Level 3
Credit Points 6
Student Contribution Band SCA Band 2
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).

Class Timetable View Unit Timetable
Residential School No Residential School

Unit Availabilities from Term 1 - 2025

Term 1 - 2025 Profile
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).

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.

Assessment Tasks

This information will not be available until 8 weeks before term.
To see assessment details from an earlier availability, please search via a previous term.

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

Past Exams

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Previous Feedback

Term 1 - 2024 : The overall satisfaction for students in the last offering of this course was 100.00% (`Agree` and `Strongly Agree` responses), based on a 25% response rate.

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.

Source: Students and teaching staff's feedback
Feedback
The Visual DSS is a complex tool to implement decision-making practices. More guidance and practices could be provided
Recommendation
Review the lab exercises that use the Virtual DSS tool and enhance guidance by incorporating additional exercises alongside recorded tutorial videos.
Action Taken
The detailed guidance has been provided in Week 2 and 4 with the recorded videos to illustrate how to build business analytic models and perform risk analysis.
Source: Teaching team's feedback
Feedback
Some tutorial exercises and lab practices should be adjusted to align with the updated lecture slides
Recommendation
Review the tutorial material and refresh the existing exercises/practices to align with the updated textbook and the lecture slides.
Action Taken
The lecture slides and tutorial practices have been updated, and tutorial videos (recorded based on the updated lecture contents with the emerging BI technologies and applications) have been regenerated to match the lecture contents well.
Source: Student feedback and Unit Coordinator reflection
Feedback
Online students find it difficult to attend workshops during the day due to work commitments
Recommendation
Conduct online workshops in the evenings or afternoons.
Action Taken
This was not actioned due to difficulties with timetabling. However, the Unit Profile stated the need to attend the online workshops in Weeks 11 and 12.
Source: Students and teaching team's feedback
Feedback
Lack of sufficient preparation for the online workshops to build business intelligence frameworks.
Recommendation
Add several tutorial activities in the weeks leading up to the online workshops.
Action Taken
In Progress
Source: Teaching Team
Feedback
No real data was used for data visualisation and dashboard design.
Recommendation
Utilise the university's IoT facilities to conduct data virtualisation and dashboard design based on the built IoT applications and the IoT web services.
Action Taken
In Progress
Unit learning Outcomes
This information will not be available until 8 weeks before term.
To see Learning Outcomes from an earlier availability, please search via a previous term.