DATA WAREHOUSE CONCEPTS AND DESIGN
CSE5DWD
2019
Credit points: 15
Subject outline
This subject introduces students to evolution of data warehouse technology, data warehouse terms and concepts, data warehouse design, data sourcing, organisational issues involved with designing and implementing a data warehouse. Especially, the multidimensional modelling with various data warehouse design schemas such as star schema and snowflake schema are the foci of the subject. Furthermore, related important technologies of Extract-Transformation-Load (ETL) system including 34 subsystems are discussed and studied. The different Online Analytical Processing (OLAP) architectures and approaches are analysed, compared and evaluated in the subject. The research issues on the performance of data warehouse and OLAP techniques are discussed and investigated. Several real world case studies are used to explain and illustrate various aspects of this subject.
School: School Engineering&Mathematical Sciences
Credit points: 15
Subject Co-ordinator: Jinli Cao
Available to Study Abroad Students: Yes
Subject year level: Year Level 5 - Masters
Exchange Students: Yes
Subject particulars
Subject rules
Prerequisites: BUS5BID or CSE2DBF or CSE4DBF or admitted into Master of Business Information Management and Systems
Co-requisites: N/A
Incompatible subjects: CSE4DWD
Equivalent subjects: N/A
Special conditions: N/A
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | The Data Warehouse Toolkit | Prescribed | Kimball, R and Ross, M, 2013 | WILEY |
| Readings | The Data Warehouse Lifecycle Toolkit, 2nd ed | Recommended | Kimball, R, et al | WILEY, 2008 |
Graduate capabilities & intended learning outcomes
01. Comprehensively design a suitable data warehouse solution using various dimensional modelling techniques for a given problem
- Activities:
- Lab class and lecture discussions, assignment practice and online learning
02. Critically appraise and compare different data warehouse modelling approaches for real world industry projects
- Activities:
- Lab class and lecture discussions, assignment practice and online learning
03. Extract, transform and load source data for a data warehouse.
- Activities:
- Lab class and Lecture discussions; assignment practice.
04. Critique Online Analytical Processing performance on different data warehouse architectures
- Activities:
- Lab class and lecture discussions, online learning
05. Evaluate data warehouse design to improve the user's satisfaction level
- Activities:
- Lab class and lecture discussions, assignment practice and online learning
Melbourne, 2019, Semester 1, Blended
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Enrolment information:
Subject Instance Co-ordinator: Jinli Cao
Class requirements
Unscheduled Online ClassWeek: 10 - 22
One 3.0 hours unscheduled online class per week on weekdays during the day from week 10 to week 22 and delivered via online.
Laboratory ClassWeek: 10 - 22
One 2.0 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| One assignment - data warehouse design using dimensional modelling techniques (equiv to 1800 words) | 30 | 01, 02, 03, 05 | |
| One 2-hour examination | Hurdle requirement: To pass the subject, a pass in the examination is mandatory. This is to meet basic knowledge requirement for the subject. | 50 | 01, 02, 03, 04 |
| Ten weekly online quizzes (each quiz lasts for 10 minutes, 1700 words equivalent total) | 20 | 01, 02, 03, 04, 05 |