FIT5097 - Business intelligence modelling - 2019

6 points, SCA Band 2, 0.125 EFTSL

Postgraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.


Information Technology

Chief examiner(s)

Associate Professor David Dowe

Unit guides



  • Second semester 2019 (On-campus)


At least one quantitative unit (such as Mathematics or Statistics) in an undergraduate degree.




Monash Online offerings are only available to students enrolled in the Graduate Diploma in Data ScienceGraduate Diploma in Data Science ( via Monash Online.


This unit introduces students to the principles, techniques and applications of computer-based decision support models for business and industry. Topics include: decision trees; linear programming and optimisation; other mathematical programming methods; waiting lines and queues; time series analysis and forecasting; inventory modelling and discrete-event simulation. Models will be built and solved using spreadsheets or other computer applications as appropriate.


On completion of this unit, students should be able to:

  1. explain a variety of techniques for modelling business decision problems;
  2. choose the appropriate decision model for a particular problem;
  3. set up simple models and solve with hand calculations;
  4. set up mathematical models for solution in a spreadsheet or other application software;
  5. validate models and conduct a sensitivity analysis;
  6. analyse a real problem and report the results;
  7. explain the difficulty of applying models to real situations - which often requires that approximations, simplifications and generalisations be made;
  8. explain the approximate nature of some types of business modelling and why this usually means that a sensitivity analysis needs to be conducted.


NOTE: From 1 July 2019, the duration of all exams is changing to combine reading and writing time. The new exam duration for this unit is 2 hours and 10 minutes.

Examination (2 hours and 10 minutes): 60%; In-semester assessment: 40%

Workload requirements

Minimum total expected workload equals 12 hours per week comprising:

  1. Contact hours for on-campus students:
    • Two hours of lectures
    • One 2-hour laboratory
  2. Additional requirements (all students):
    • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

This unit applies to the following area(s) of study