Note: This is an archived Handbook entry from 2015.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2015:April, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 30 hours |
Total Time Commitment: Not available
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|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
The aim of business intelligence is to teach students how to extract relevant information from large amounts of data to make improved business decisions.
Big data is big business, but there are not enough managers who can ask the right questions and interpret the results of analysis effectively. The McKinsey report predicts a need for an additional 1.5 million adequately trained managers in the US alone. Data-Mining is the science of extracting useful information from large datasets. It is the process of quantifying the dependency between outcomes and using that knowledge to predict future outcomes. Data-mining is used in all business related fields.
On completion of this subject the student should be able to:
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
Master of Business Administration |
Master of Business Administration
Download PDF version.