Data Analytics and Business Intelligence PG (8697.4)
|Available teaching periods||Delivery mode||Location|
|View teaching periods|| On-Campus
|| Bruce, Canberra
|0.125||3||Faculty Of Science And Technology|
|Discipline||Study level||HECS Bands|
|Academic Program Area - Technology||Post Graduate Level|| Band 1 2021 (Commenced After 1 Jan 2021)
Band 1 2021 (Commenced Before 1 Jan 2021)
Learning outcomesOn 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 attributes1. UC graduates are professional - communicate effectively
1. 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
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - think globally about issues in their profession
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
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
Prerequisites6554 Introduction to Statistics G or a similar unit.
Incompatible units8696 Data Analytics and Business Intelligence.
|Year||Location||Teaching period||Teaching start date||Delivery mode||Unit convener|
|2023||Bruce, Canberra||Semester 2||31 July 2023||On-Campus||Dr Ghazal Bargshady|
|2024||Bruce, Canberra||Semester 2||29 July 2024||On-Campus||Dr Yibe Alem|
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%)
High Distinction (HD)
Note: Quiz 4 and Assignment assessment items for PG students slightly vary from those for UG students to address the additional graduate attributes and learning outcomes.
Students have a responsibility to uphold University standards on ethical scholarship. Good scholarship involves building on the work of others and use of others' work must be acknowledged with proper attribution made. Cheating, plagiarism, and falsification of data are dishonest practices that contravene academic values. Refer to the University's Student Charter for more information.
To enhance understanding of academic integrity, all students are expected to complete the Academic Integrity Module (AIM) at least once during their course of study. You can access this module within UCLearn (Canvas) through the 'Academic Integrity and Avoiding Plagiarism' link in the Study Help site.
Use of Text-Matching Software
The University of Canberra uses text-matching software to help students and staff reduce plagiarism and improve understanding of academic integrity. The software matches submitted text in student assignments against material from various sources: the internet, published books and journals, and previously submitted student texts.
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.
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
Familiarity with 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.
Textbook purchase and some printing costs are anticipated.
Work placement, internships or practicums
Not applicable to this unit.
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 email@example.com 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).
- Semester 2, 2023, On-Campus, UC - Canberra, Bruce (213675)
- Semester 2, 2022, On-Campus, UC - Canberra, Bruce (207216)
- Semester 2, 2021, On-Campus, UC - Canberra, Bruce (202065)
- Semester 2, 2020, On-Campus, UC - Canberra, Bruce (195585)
- Semester 1, 2020, On-Campus, UC - Canberra, Bruce (193957)
- Semester 2, 2019, On-Campus, UC - Canberra, Bruce (185310)
- Winter Term, 2019, On-Campus, UC - Canberra, Bruce (185605)
- Semester 2, 2018, On-Campus, UC - Canberra, Bruce (182358)
- Winter Term, 2018, On-Campus, UC - Canberra, Bruce (182355)