Data Analytics and Business Intelligence (8696.4)
Available teaching periods | Delivery mode | Location |
---|---|---|
View teaching periods | On-campus |
Bruce, Canberra |
EFTSL | Credit points | Faculty |
0.125 | 3 | Faculty Of Science And Technology |
Discipline | Study level | HECS Bands |
Academic Program Area - Technology | Level 3 - Undergraduate Advanced Unit | Band 1 2021 (Commenced After 1 Jan 2021) Band 1 2021 (Commenced Before 1 Jan 2021) |
Learning outcomes
On successful completion of this unit, students will be able to:1. Source and access data from a variety of databases;
2. Select and apply appropriate tools for data visualization;
3. Select and apply descriptive data analytics methods;
4. Select and apply predictive data analytics methods;
5. Fit statistical models; and
6. Use the results to produce business intelligence in a variety of settings.
Graduate attributes
1. UC graduates are professional - communicate effectively1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - take pride in their professional and personal integrity
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - evaluate and adopt new technology
Prerequisites
11723 Data Analysis Skills for Science OR 6540 Introduction to StatisticsCorequisites
None.Incompatible units
8697 Data Analytics and Business Intelligence PGEquivalent units
None.Assumed knowledge
None.Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
---|---|---|---|---|---|
2024 | Bruce, Canberra | Semester 2 | 29 July 2024 | On-campus | Dr Ghazal Bargshady |
2025 | Bruce, Canberra | Semester 2 | 28 July 2025 | On-campus | Dr Ghazal Bargshady |
Required texts
Tan, P. N. (2019). Introduction to data mining, second edition (required - available for purchase at The School Locker)
Williams, G. (2011). Data mining with Rattle and R: The art of excavating data for knowlegde discovery (recommended reading)
Larose, D. T. (2005). Discovering Knowledge in Data: an Introduction to Data Mining (recommended reading)
Submission of assessment items
Special assessment requirements
An aggregate mark of 50% is required to pass the unit.
Your final grade will be determined as follows:
Final mark (100%) = Quiz 1 (5%) + Quiz 2 (10%) + Quiz 3 (10%) + Quiz 4 (15%) + Assignment (35%) + Presentations (20%) + Engagement (5%)
Grade |
Numerical Grade |
Pass (P) |
50-64 |
Credit (CR) |
65-74 |
Distinction (DI) |
75-84 |
High Distinction (HD) |
85-100 |
Students must apply academic integrity in their learning and research activities at UC. This includes submitting authentic and original work for assessments and properly acknowledging any sources used.
Academic integrity involves the ethical, honest and responsible use, creation and sharing of information. It is critical to the quality of higher education. Our academic integrity values are honesty, trust, fairness, respect, responsibility and courage.
UC students have to complete the Academic Integrity Module annually to learn about academic integrity and to understand the consequences of academic integrity breaches (or academic misconduct).
UC uses various strategies and systems, including detection software, to identify potential breaches of academic integrity. Suspected breaches may be investigated, and action can be taken when misconduct is found to have occurred.
Information is provided in the Academic Integrity Policy, Academic Integrity Procedure, and University of Canberra (Student Conduct) Rules 2023. For further advice, visit Study Skills.
Learner engagement
A total workload of 150 hours include 24 hours of lectures, 22 hours of tutorials, 24 hours of preview/review time for lectures and tutorials, a total of 28 hours of preparation and attempt time for 4 quizzes, and 48 hours for assignment and 4 hours for preparing for presentations. The stated hours include the time required to attempt/present assessment items.
Participation requirements
Your participation in both class and online activities will enhance your understanding of the unit content and results in a better learning experience and achievement. Lack of participation may result in your inability to satisfactorily pass assessment items.
Required IT skills
Report writing skill and basic computer use as well as exposure to programming is assumed as the statistical programming language R (with Rattle GUI) will be used for the lab activities.
This unit may involve online meetings in real time using the Virtual Room in your UCLearn teaching site. The Virtual Room allows you to communicate in real time with your lecturer and other students. To participate verbally, rather than just typing, you will need a microphone. For best audio quality we recommend a microphone and speaker headset. For more information and to test your computer, go to the Virtual Room in your UCLearn site and 'Join Course Room'. This will trigger a tutorial to help familiarise you with the functionality of the virtual room.
In-unit costs
Textbook purchase and some printing costs are anticipated.
Work placement, internships or practicums
Not applicable to this unit.
Additional information
Provision of information to the group
Communications and announcements throughout the term will be made to the whole class through Canvas Announcements or the Canvas Discussion Forums. It is the responsibility of the student to ensure that they check for announcements on the unit's Canvas website. Students should ensure they check their student email regularly. The Discussion Forum will be checked by staff regularly.
Use of student email account
The University Email policy states that "students wishing to contact the University via email regarding administrative or academic matters need to send the email from the University account for identity verification purposes". Therefore all unit enquiries should be emailed using a student university email account. Students should contact servicedesk@canberra.edu.au if they have any issues accessing their university email account.
In all cases of absence, sickness or personal problems it is the student's responsibility to ensure that the Unit Convener is informed. The minimum participation requirement must be met in order to pass the unit (regardless of supporting documentation).
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