This course builds on the material introduced in INFS7040 Electronic Commerce for Managers and INFS7007 Systems Analysis & Modelling by covering how business analytics and business intelligence can be used for improved business decision-making. Contemporary forms of analytics such as visual, text, sentiment, web, and social are covered in the course, as well as established technologies like decision support, knowledge management, collaborative and expert systems.
Upon successful completion, students will have the knowledge and skills to:Upon successful completion of the requirements for this course, students will be able to:
- Identify the business problems that require decision-making support from business analytics;
- Establish the best search strategy to acquire evidence relevant to the business problem;
- Establish the business analytics method relevant to the business process and the reliability and validity of evidence;
- Summarise the relevant evidence in view of finding analytics solutions to business questions;
- Recognise social and ethical implications of analytics solutions to the business problem;
- Design optimal analytics processes to increase the likelihood of favourable business decision-making outcomes; and
- Reflect on feedback from self-reflection journal to adjust solutions.
Indicative AssessmentThe following is the proposed assessment, with the final assessment being decided by end of Week1.
Weekly Assessment - Weekly practical exercises and test bank questions - Due Weekly - Worth 30% Reflective Journal - A reflective weekly summary of your learning progress - Due Weekly - Worth 10% Visualization Assignment - Small report demonstrating how data visualization can be used by a real-life organization Friday - Due end of Week 6 - Worth 20%
Major Assignment – Final Report - Large final report in case study format summarising how business analytics can be applied by a real-life organization. - Due Friday first week of exam period - Worth 40%
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
WorkloadStudents taking this course are expected to commit at least 10 hours per week to completing the work. This will include 3 hours per week in class and at least 7 hours a week on average (including non-teaching weeks) on course reading, research, writing and assessment work.
Prescribed TextsBusiness Intelligence and Analytics: Systems for Decision Support (10th Global Edition) 2014, Turban, E., Sharda, R., and Delen, D., Pearson, ISBN: 9781292009209
Assumed KnowledgeStudents attempting this course are assumed to have done an introductory information systems course (e.g. INFS7004 or INFS7007 or INFS7040) or possess basic background knowledge of information systems.
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|5060||19 Feb 2018||27 Feb 2018||31 Mar 2018||25 May 2018||In Person||N/A|