ITC516 Data Mining and Visualisation for Business Intelligence (8)
CSU Discipline Area: Computing (COMPU)
Duration: One session
Abstract:
This subject is designed to provide students with knowledge of the principles of data mining and visualisation of datasets for Business Intelligence. It focuses on the need for developing timely and accurate views of large datasets and the need for the creation of visual displays, or dashboards, to present accurate views of complex data trends and patterns. Students who undertake this subject are expected to have a basic working knowledge of database theory and operations.
+ Subject Availability Modes and Locations
| Session 3 | |
|---|---|
| Distance | Wagga Wagga |
Continuing students should consult the SAL for current offering details: ITC516
Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.
Prerequisite(s):
Enrolment restrictions:
For students in Master of Systems Development, Master of Database Design and Management, Master of Information Systems Security, Graduate Certificate in Systems Development, Graduate Certificate in Database Design and Management, Graduate Certificate in Information Systems Security only.
Objectives:
Upon successful completion of this subject, students should:
- Be able to design database systems with large datasets using the principles of database theory
- Be able to identify, analyse and implement business requirements for the identification of trends and patterns in datasets
- Be able to design and implement data views and dashboards using data visualisation principles
- Be able to select the correct predictive analysis techniques to apply to a dataset
- Be able to analyse the data integrity and security requirements for large datasets
- Be able to identify and discuss the security, privacy and ethical implications involved in data mining and predictive analysis
- Be able to develop and refine database structures for unstructured data using XML or NOSQL databases
- Be able to discuss the importance of current and future trends likely to affect data mining and visualisation
Syllabus:
The subject will cover the following topics:
- Database theory for large datasets including CAP theorem, XML and NOSQL databases
- Data mining techniques to identify trends and patterns
- Predictive analysis techniques for data mining
- Data visualisation principles and techniques
- Building data dashboards
- Security, privacy and ethical implications involved in data mining and predictive analysis
- Issues and trends in unstructured data, data mining and visualisation
The information contained in the 2013 CSU Handbook was accurate at the date of publication: 24 April 2013. The University reserves the right to vary the information at any time without notice.