cse4dwd data warehse concpt and design
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
Learning resources
Readings
Resource Type | Title | Resource Requirement | Author and Year | Publisher |
---|---|---|---|---|
Readings | The Data Warehouse Toolkit | Prescribed | Kimball, R and Ross, M | WILEY 2002 |
Readings | The Data Warehouse Lifecycle Toolkit, 2nd ed | Recommended | Kimball, R, et al | WILEY, 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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Melbourne, 2015, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorJinli Cao
Class requirements
Computer LaboratoryWeek: 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.
LectureWeek: 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 element | Comments | % | ILO* |
---|---|---|---|
one 3-hour examination | 70 | 01, 02, 03, 04, 05 | |
one assignment - data warehouse design using dimensional modelling techniques | In 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 |