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PRT531 - Business Intelligence and Data Mining

2025

Sector

Higher Education

Discipline

Information Technology

Credit Points

Equivalent Units

(BIS551)

Prerequisites

Incompatible

Coerequisites

Assumed Knowledge

PRT451 or PRT581

Unit Description

This unit is designed to equip students with the knowledge and skills to operate in an effective and professional way in applying Business Intelligence (BI) and Data Mining to organizations. The unit will address BI and Data Mining from a data/information/knowledge perspective. Other specific areas covered in the unit include diverse BI applications, data mining, text and web mining, and the relationships between BI and Data Mining. Students will have the opportunity to analyze and transform data into knowledge that is applicable to decision making in organization. Students must have access to a reliable high-speed broadband connection.

Unit Learning Outcomes

1.	Apply an advanced understanding of Business Intelligence and its importance for organizational success and competitiveness.
2.	Critically analyze decision making processes to identify specific problems in an organisation.
3.	Investigate the role and importance of Data Mining, data warehouse, data mart and metadata and knowledge in Business Intelligence.
4.	Critically evaluate current techniques to turn data/information into knowledge for purposes of using that knowledge to help develop Business Intelligence systems.
5.	Critically evaluate efficient and effective solutions to identified problems using Business Intelligence concepts, Data Mining techniques and data/information/knowledge modelling techniques.
6.	Apply analytical thinking in setting up business intelligence system and in identifying novel data mining techniques.

Assessment Overview

	Assessment Task	Value (of total mark)	Related Learning Outcome/s
1.	Business Intelligence Online Quiz (30 minutes)	10%	1,2,4
2.	Group Assignment BI and Data Mining (1500 words per student)	25%	1,2,3,4,5,6
3.	Online Test (2 hours)	25%	2,3,4
4.	Group Final Assignment BI and Data Mining (2000 words per student)	40%	1,2,3,4,5,6

Unit Availability

Year	Semester	Att Mode	Location	Learning Method	Timetable*
2025	Semester 1	Internal	CDU Sydney	OLR	View
2025	Semester 1	Internal	Danala - Education and Community Precinct	OLR	View
2025	Semester 1	External	External Studies	OLR	View

* Timetable will be displayed in new tab or window depending on your browser's configuration; ensure Pop-ups are allowed for this site to view the timetable.

OLR: Internet access is required for this unit as students are required to access study materials provided on-line through Learnline. Please log into Learnline on the first day of each teaching period. For more information about Learnline, please click here.

Critical Dates

Important Dates for Students

Fee Information:
Fees and Payments
Student Services and Amenities Fees
2025 Domestic Unit Fees (PDF)
2025 Incidental Fees (PDF)