Data Warehousing (ISYS90086)
Graduate courseworkPoints: 12.5Not available in 2022
From 2023 most subjects will be taught on campus only with flexible options limited to a select number of postgraduate programs and individual subjects.
To learn more, visit COVID-19 course and subject delivery.
About this subject
Overview
| Fees | Look up fees |
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AIMS
Data warehouses are designed to provide organisations 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.
Students who have a weighted average mark of at least 75% in the Master of Information Systems have the option to complete the on-line Advanced Elective ISYS90094 Business Analysis and Decision Making instead of ISYS90086 Data Warehousing.
INDICATIVE CONTENT
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.
Intended learning outcomes
- Describe the scope and application of data warehousing in organisations
- Evaluate the appropriateness of data warehousing initiatives in organisations
- Design data warehouse solutions
- Explain and illustrate the intricacies of the data integration problem
- Communicate the role of data warehousing in organisations
- Understand the issues around data quality, privacy and metadata and how these issues affect data warehousing initiatives
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
Last updated: 12 November 2022
Eligibility and requirements
Prerequisites
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| INFO90002 | Database Systems & Information Modelling |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| ISYS90094 | Business Analytics and Decision Making | Term 3 (Online) |
12.5 |
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 12 November 2022
Assessment
| Description | Timing | Percentage |
|---|---|---|
Part A: A data warehouse design case study paper (25%) of approximately 5000 words requiring approximately 32-37 hours of work per student. Due after the 4th day of teaching (equivalent week 9). Intended Learning Outcomes (ILO's) 1, 2, 3 and 5 are addressed in this part of the assessment.
| Week 9 | 25% |
Part B: A report (25%) of approximately 4000 words requiring approximately 32-37 hours of work per student. Due after the 6th day of teaching (equivalent week 12). ILO's 3, 4, 5 and 6 are addressed in this part of the assessment.
| Week 12 | 25% |
One written 2 hour closed book end of semester examination (50%). ILO's 1 to 6 are addressed in the examination.
| End of semester | 50% |
Additional details
Last updated: 12 November 2022
Dates & times
Not available in 2022
Time commitment details
200 hours
Last updated: 12 November 2022
Further information
- Texts
- Subject notes
LEARNING AND TEACHING METHODS
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.
INDICATIVE KEY LEARNING RESOURCES
All required readings are available via the LMS.
CAREERS / INDUSTRY LINKS
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 Handbook entries
This subject contributes to the following:
Type Name Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required.
- Available to Study Abroad and/or Study Exchange Students
Last updated: 12 November 2022