- Code INFS8210
- Unit Value 6 units
- Offered by Research School of Management
- ANU College ANU College of Business and Economics
- Course subject Information Systems
- Academic career PGRD
- Dr Alexander Richardson
- Mode of delivery In Person
Second Semester 2017
See Future Offerings
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%
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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.
Requisite and Incompatibility
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.
- Domestic fee paying students
- International fee paying students
Offerings, Dates and Class Summary Links
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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|
|9920||24 Jul 2017||31 Jul 2017||31 Aug 2017||27 Oct 2017||In Person||N/A|