Overview
The techniques of data science used to produce predictive and adaptive decision support techniques with particular emphasis on prediction, optimisation and search methods.
All businesses make decisions based on an understanding of their historical, current and predicted environments. Adaptive Business Intelligence introduces methods for supporting robust decision making in a business context, leading to graduates with the confidence to visualise, understand and predict relevant aspects of a business process. Given the future of improving business processes is to understand what has happened and what will happen, INFO 424 delivers some fundamental skills that all business graduates need.
About this paper
| Paper title | Adaptive Business Intelligence |
|---|---|
| Subject | Information Science |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period(s) | Semester 1
(On campus)
Semester 1 (Distance learning) |
| Domestic Tuition Fees ( NZD ) | $1,535.64 |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Prerequisite
- BSNS 102 or STAT 110
- Restriction
- INFO 304, INFO 324
- Limited to
- MA, MCom, MSc, MAppSc, MBusDataSc, BA(Hons), BAppSc(Hons), BCom(Hons), BSc(Hons), PGDipAppSc , PGDipArts, PGDipSci, PGCertAppSc
- Contact
- peter.whigham@otago.ac.nz
- Teaching staff
Convener and Lecturer: Associate Professor Peter Whigham
- Paper Structure
- The paper covers three main themes:
- Visualisation of data
- Model building for prediction and analyses
- Business applications
- Textbooks
"An Introduction to Statistical Learning", by G.James, D. Witten, T. Hastie & R. Tibshirani. This textbook is available online through the library.
- Course outline
- View the most recent Course Outline
- Graduate Attributes Emphasised
- Interdisciplinary perspective, Scholarship, Communication, Critical thinking, Information literacy, Self-motivation.
View more information about Otago's graduate attributes. - Learning Outcomes
Students who successfully complete this paper will:
- Have the ability to identify the activities of prediction, optimisation and adaption that exist within a decision-making context
- Be confident in applying methods to understand and critically assess these activities
- Have the technical skills to handle data processing, visualisation, modelling and interpretation