2011/2 Provisional Module Catalogue - UNDER CONSTRUCTION & SUBJECT TO CHANGE
Module Code: COMM033
Module Title: DATABASE AND KNOWLEDGE DISCOVERY
Module Provider: Computing
Short Name: COMM033
Level: M
Module Co-ordinator: VRUSIAS BL Dr (Computing)
Number of credits: 15
Number of ECTS credits: 7.5
Module Availability
Spring Semester
Assessment Pattern
Unit(s) of Assessment
Weighting Towards Module Mark( %)
Group Coursework (2-3 students per group):
Modelling and implementing a database system capable of performing data mining on the stored data, in order to discover useful patterns.
50
Exam
Closed book examination
50
Qualifying Condition(s)
A weighted aggregate mark of 50% is required to pass the module.
Module Overview
A database system is the core part in information systems and most modern applications in general and it is a vital component of a system that can determine its performance and security. When developing information systems, great emphasis should be put into the way that the database is designed, implemented, configured and administered. Furthermore, state-of-the art add-on and plug-in database components can enrich the system with data mining and information retrieval capabilities.
Prerequisites/Co-requisites
Module Aims
The main aim of this module has two purposes. The first is to develop the necessary skills and familiarity to use state-of-the-art technologies to design, implement and manage a database system, and the second is to use data mining and information retrieval tools to discover data patterns and retrieve information from the database.
Learning Outcomes
By the end of the module the students should be able to:
design and implement a database system based on given requirements
administer and secure a database system
understand data mining techniques and be able to choose the appropriate one to analyse data and retrieve useful patterns
use information retrieval techniques to store and retrieve multimedia data
work in a group to model and develop a comprehensive database system based on specified requirements
Module Content
Introduction to database systems:
Relational databases
Object-oriented databases
Popular databases: Oracle, MySQL, Microsoft SQL Server
SQL
Business intelligence
Design
Relational models and data structure
Design verification (normalisation) and revision (optimisation)
Implementation
Working with primitive data types
Working with data objects
Functions
Transactions
XML
Administration
Connection pooling, scalability, security
Data mining
Data warehousing
Understand how, when, and where to use data mining techniques
Discovering data patterns in raw data
Information Retrieval
Storing unstructured and multimedia data
Retrieving multimedia data
Methods of Teaching/Learning
The module will consist of approximately 20 hours of lectures and 10 hours of lab sessions.
Selected Texts/Journals
Recommended books are:
Rob, P., Coronel, C. and Crockett, K., Database Systems: Design, Implementation & Management - International Edition, Thomson Learning, 2008, ISBN: 1844807320
MacLennan J., Tang Z. H. and Crivat, B., Data Mining with Microsoft SQL Server 2008, John Wiley & Sons, 2008, ISBN: 0470277742
