DATA WAREHOUSE CONCEPTS AND DESIGN

CSE4DWD

2015

Credit points: 15

Subject outline

Data warehouse underpins most enterprise systems like enterprise resource planning, customer relationship management and supply chain management systems. A data warehouse is designed to provide information from a variety of sources within and outside an organisation to the enterprise systems. 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 focuses of the subject. Furthermore, the related important technologies of Extract-Transformation-Load (ETL) system and Online Analytical Processing (OLAP) approaches are discussed in the subject. Several real world case studies are used to explain and illustrate various aspects of this subject.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorJinli Cao

Available to Study Abroad StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Exchange StudentsYes

Subject particulars

Subject rules

PrerequisitesN/A

Co-requisites BUS5BID

Incompatible subjects CSE4ADB

Equivalent subjectsN/A

Special conditionsN/A

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsThe Data Warehouse ToolkitPrescribedKimball, R and Ross, MWILEY 2002
ReadingsThe Data Warehouse Lifecycle Toolkit, 2nd edRecommendedKimball, R, et alWILEY, 2008

Graduate capabilities & intended learning outcomes

01. Explain the role of the data warehouse within an enterprise system

Activities:
Learning from lectures 1 & 2, 11 -12. Discussing research issues and current trend of DW usages in labs
Related graduate capabilities and elements:
Ethical Awareness (Ethical Awareness)
Inquiry/ Research (Inquiry/ Research)
Critical Thinking (Critical Thinking)
Writing (Writing)
Creative Problem-solving (Creative Problem-solving)

02. Analyse a given problem and design a suitable data warehouse solution using various dimensional modelling techniques

Activities:
Students will be given a large assignment for building a data warehouse application Lectures 2-5 are on Star Schema, Snow flaking schema modelling techniques for dimensional modelling. Many case studies are discussed in lectures and 5 labs
Related graduate capabilities and elements:
Critical Thinking (Critical Thinking)
Ethical Awareness (Ethical Awareness)
Writing (Writing)
Creative Problem-solving (Creative Problem-solving)
Discipline-specific GCs (Discipline-specific GCs)

03. Explain and recommend solutions for the issues involved with sourcing data for the data warehouse tool

Activities:
Learning the process of Extract-Transform-Load (ETL) activities for various data sources in lectures and practising on the tool of Oracle Data warehouse design centre. We have 3 laboratories to practise on the tools.
Related graduate capabilities and elements:
Discipline-specific GCs (Discipline-specific GCs)
Critical Thinking (Critical Thinking)
Creative Problem-solving (Creative Problem-solving)
Inquiry/ Research (Inquiry/ Research)

04. Query a data warehouse using an OLAP reporting tool

Activities:
Introduce the concept of OLAP in lecture. Discussing the techniques learned in the lecture and tutorials. Practising in two Labs.
Related graduate capabilities and elements:
Inquiry/ Research (Inquiry/ Research)
Discipline-specific GCs (Discipline-specific GCs)
Critical Thinking (Critical Thinking)
Creative Problem-solving (Creative Problem-solving)
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)

05. Explain the principle involved in managing a data warehouse project

Activities:
Learning the concepts in lectures 11 & 12 and discussing the design and implementation issues in Labs
Related graduate capabilities and elements:
Discipline-specific GCs (Discipline-specific GCs)
Creative Problem-solving (Creative Problem-solving)
Quantitative Literacy/ Numeracy (Quantitative Literacy/ Numeracy)
Inquiry/ Research (Inquiry/ Research)
Critical Thinking (Critical Thinking)

Subject options

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Start date between: and    Key dates

Melbourne, 2015, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorJinli Cao

Class requirements

Computer Laboratory Week: 10 - 22
One 2.0 hours computer laboratory per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
one 3-hour examination70 01, 02, 03, 04, 05
one assignment - data warehouse design using dimensional modelling techniquesIn order to pass the subject, students must attend at least 70% of the laboratory classes and must obtain an overall pass grade, pass the examination and pass the overall non-examination components.30 01, 02, 03, 04, 05