Big Data in Marketing (12054.1)
Please note these are the 2024 details for this unit
Available teaching periods | Delivery mode | Location |
---|---|---|
View teaching periods | On-Campus Online |
Bruce, Canberra |
EFTSL | Credit points | Faculty |
0.125 | 3 | Faculty Of Business, Government & Law |
Discipline | Study level | HECS Bands |
Canberra Business School | Level 3 - Undergraduate Advanced Unit | Band 4 2021 (Commenced After 1 Jan 2021) Band 4 2021 (Commenced After 1 Jan Social Work_Exclude 0905) Band 5 2021 (Commenced Before 1 Jan 2021) |
The course will provide students with an understanding of the conceptual foundations of Big Data. It will unpack important concepts and techniques such as data visualization, machine learning, statistical analysis, and data-driven marketing strategies. Furthermore, students will critically reflect on the ethical aspects of big data. Throughout the course, students will explore various types of big data, including data from websites, social media, and search engines, and focus on the 5Vs of big data: volume, velocity, variety, veracity, and value. This course will also provide students with hands-on experience with big data analytics in a marketing setting.
1. Define the role of big data in contemporary marketing practices;
2. Apply big data analysis tools to develop customer insight and undertake marketing decisions;
3. Critically reflect on the ethical aspects of big data including privacy and security; and
4. Create data driven marketing strategies.
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
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
4. UC graduates are able to demonstrate Aboriginal and Torres Strait Islander ways of knowing, being and doing - use Indigenous histories and traditional ecological knowledge to develop and augment understanding of their discipline
Learning outcomes
After successful completion of this unit, students will be able to:1. Define the role of big data in contemporary marketing practices;
2. Apply big data analysis tools to develop customer insight and undertake marketing decisions;
3. Critically reflect on the ethical aspects of big data including privacy and security; and
4. Create data driven marketing strategies.
Graduate attributes
1. UC graduates are professional - communicate effectively1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
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
4. UC graduates are able to demonstrate Aboriginal and Torres Strait Islander ways of knowing, being and doing - use Indigenous histories and traditional ecological knowledge to develop and augment understanding of their discipline
Prerequisites
11176 Marketing FundamentalsCorequisites
None.Incompatible units
None.Equivalent units
None.Assumed knowledge
None.
Availability for enrolment in 2024 is subject to change and may not be confirmed until closer to the teaching start date.
Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
---|---|---|---|---|---|
2024 | Bruce, Canberra | Semester 2 | 29 July 2024 | On-Campus | Dr Johra Fatima |
2024 | Bruce, Canberra | Semester 2 | 29 July 2024 | Online | Dr Johra Fatima |
The information provided should be used as a guide only. Timetables may not be finalised until week 2 of the teaching period and are subject to change. Search for the unit
timetable.