DATA WAREHOUSE CONCEPTS AND DESIGN

CSE5DWD

2021

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.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorJinli Cao

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

Prerequisites BUS5BID or CSE2DBF or CSE4DBF or admitted into Master of Business Information Management and Systems

Co-requisitesN/A

Incompatible subjectsCSE4DWD

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

The Data Warehouse Toolkit

Resource TypePrescribed

Resource RequirementN/A

AuthorKimball, R and Ross, M

Year2013

Edition/VolumeN/A

PublisherWILEY

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

The Data Warehouse Lifecycle Toolkit

Resource TypeRecommended

Resource RequirementN/A

AuthorKimball, R, et al

Year2008

Edition/VolumeN/A

PublisherWILEY

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Career Ready

Career-focusedNo

Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Comprehensively design a suitable data warehouse solution using various dimensional modelling techniques for a given problem
02. Critically appraise and compare different data warehouse modelling approaches for real world industry projects
03. Extract, transform and load source data for a data warehouse.
04. Critique Online Analytical Processing performance on different data warehouse architectures
05. Evaluate data warehouse design to improve the user's satisfaction level

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorJinli Cao

Class requirements

Laboratory ClassWeek: 10 - 22
One 2.00 h 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 h 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 h unscheduled online class per week on weekdays during the day from week 10 to week 22 and delivered via online.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
One assignment - data warehouse design using dimensional modelling techniques (equiv to 1800 words)N/AN/AN/ANo30 SILO1, SILO2, SILO3, SILO5
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.N/AN/AN/AYes50 SILO1, SILO2, SILO3, SILO4
Ten weekly online quizzes (each quiz lasts for 10 minutes, 1700 words equivalent total)N/AN/AN/ANo20 SILO1, SILO2, SILO3, SILO4, SILO5