DATA WAREHOUSE CONCEPTS AND DESIGN
CSE5DWD
2020
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: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Jinli Cao
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 5 - Masters
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
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
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
The Data Warehouse Lifecycle Toolkit
Resource Type: Book
Resource Requirement: Recommended
Author: Kimball, R, et al
Year: 2008
Edition/Volume: N/A
Publisher: WILEY
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
The Data Warehouse Toolkit
Resource Type: Book
Resource Requirement: Prescribed
Author: Kimball, R and Ross, M
Year: 2013
Edition/Volume: N/A
Publisher: WILEY
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Melbourne (Bundoora), 2020, Semester 1, Blended
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Jinli Cao
Class requirements
Laboratory ClassWeek: 10 - 22
One 2.00 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 1.00 hour lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Unscheduled Online ClassWeek: 10 - 22
One 3.00 hours unscheduled online class per week on weekdays during the day from week 10 to week 22 and delivered via online.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
One assignment - data warehouse design using dimensional modelling techniques (equiv to 1800 words) | N/A | N/A | No | 30 | SILO1, SILO2, SILO3, SILO5 |
One 2-hour examinationHurdle requirement: To pass the subject, a pass in the examination is mandatory.This is to meet basic knowledge requirement for the subject. | N/A | N/A | Yes | 50 | SILO1, SILO2, SILO3, SILO4 |
Ten weekly online quizzes (each quiz lasts for 10 minutes, 1700 words equivalent total) | N/A | N/A | No | 20 | SILO1, SILO2, SILO3, SILO4, SILO5 |