Data Warehousing

Subject ISYS90086 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 29-Feb-2016 to 29-May-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 11-Mar-2016
Census Date 31-Mar-2016
Last date to Withdraw without fail 06-May-2016

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours, comprising of one 3 hour seminar per week
Total Time Commitment:

200 hours





Recommended Background Knowledge:


Non Allowed Subjects:
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support:


Dr Sean Maynard


Dr Sean Maynard


Subject Overview:


Data warehouses are designed to provide organizations with an integrated set of high quality data to support decision-makers. They should support flexible and multi-dimensional retrieval and analysis of data. Topics covered include data warehousing and decision-making, data warehouse design, data warehouse implementation, data sourcing and data quality, on-line analytical processing (OLAP) and data mining, customer relationship management systems, and case studies of data warehousing practice. This subject is part of the Business Analytics stream within the Master of Information Systems.


This subject introduces the compelling need for data warehousing, data warehouse architectures, decision making, data warehouse design, data warehouse modelling, data quality, data warehouse implementation - including the Extract Transform Load (ETL) process, and data warehouse use in supporting decision making – including decision making tools and OLAP. Readings are provided for all topics that introduce real world cases on data warehousing and related areas and include the use of data warehousing for competitive advantage, success and failure stories in Data Warehousing.

Learning Outcomes:


Having completed this subject the student is expected to:

  1. Be familiar with data warehousing and its relationship to decision-making
  2. Understand the main concepts underlying data warehouse design and implementation, data quality and retrieval and analysis of data
  3. Be familiar with the role of data warehousing in customer relationship management systems

  • A group based data warehouse design case study paper (25%) with 2 group members of approximately 3000 words due mid-semester, requiring approximately 32-37 hours of work per student. Intended Learning Outcome (ILO) 2 is addressed in the case study paper.
  • A group based essay on a data warehousing topic (25%) with 2 group members of approximately 3000 words due anytime in week 12, requiring approximately 32-37 hours of work per student. ILOs 1 to 3 are addressed in the essay, depending on topic area selected.
  • One written 2 hour closed book end of semester examination (50%). ILOs 1-3 are addressed in the examination.

Hurdle requirement: To pass the subject, students must obtain:

  • at least 50% of the marks available in the non-examination based assessment
  • at least 50% of the marks available in the examination.
Prescribed Texts: None
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On completion of this subject students should have the following skills:

  • Students should develop skills in literature search and analysis, critical thinking and independent learning.


The subject is delivered in 3 hour classes. Each class will be made up of a combination of lectures, discussions and tutorial type activities. Outside class students will study the various aspects of data warehousing through prescribed readings.


All required readings are available via the LMS.


This subject is relevant to careers in data warehousing, data analysis, data mining, and information management. A guest lecturer will present at least one week’s worth of materials about data warehousing in industry.

Related Course(s): Doctor of Philosophy - Engineering
Master of Information Systems
Master of Information Systems
Master of Information Systems
Master of Operations Research and Management Science
Master of Philosophy - Engineering
Master of Science (Information Systems)
Related Majors/Minors/Specialisations: MIS Professional Specialisation
MIS Research Specialisation
MIT Health Specialisation
MIT Spatial Specialisation

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