Note: This is an archived Handbook entry from 2015.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2015:Semester 2, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 36 hours, comprising of one 2-hour lecture and one 1-hour tutorial/practical per week |
Total Time Commitment:
Achieving at least 75% in a programming competency test OR one of the following:
Study Period Commencement:
Semester 1, Semester 2
Semester 1, Semester 2
|Recommended Background Knowledge:|| |
|Non Allowed Subjects:|| |
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorDr Sean Maynard
Business analytics involves the use of data to support business decision-making. Topics covered include business decision-making, evidence-based management, data warehouse design and implementation, data sourcing and quality, on-line analytical processing (OLAP), dashboards and data mining, case studies of business analytics practice. This subject is a 3rd year breadth subject in information systems, and forms one of the elective subjects for the Diploma of Informatics.
This subject introduces the concepts of business analytics, decision making, data warehouse design, data warehouse modelling, data quality, data warehouse implementation - including the ETL process, and data warehouse use in supporting business analytics – including decision making tools and OLAP. Readings are provided for all topics that introduce real world cases on business analytics and related areas and include the use of business analytics in organisations.
Intended Learning Outcomes (ILOs)
On completion of this subject the student is expected to:
|Prescribed Texts:|| |
|Breadth Options:|| |
This subject potentially can be taken as a breadth subject component for the following courses:
You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
On completion of this subject, students should have developed the following generic skills:
Learning and Teaching Methods
The subject will be delivered through a combination of lectures and labs. Students will also complete two assignments which will reinforce the material covered in class.
Indicative Key Learning Resources
All required readings are available via the LMS.
This subject is relevant to careers in data warehousing, data analysis, data mining, and information management.
|Related Breadth Track(s):||
Information Technology in Organisations |
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