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2010/1 Module Catalogue
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.

Closed book examination

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.

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:

  1. design and implement a database system based on given requirements
  2. administer and secure a database system
  3. understand data mining techniques and be able to choose the appropriate one to analyse data and retrieve useful patterns
  4. use information retrieval techniques to store and retrieve multimedia data
  5. 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
  • Relational models and data structure
  • Design verification (normalisation) and revision (optimisation)
  • Working with primitive data types
  • Working with data objects
  • Functions
  • Transactions
  • XML
  • 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
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