Database systems are the most widely used software systems in commerce and industry. Database management systems are used to store and manage the complex integrated information resources of organisations. This module introduces the theoretical and practical issues relating to the design and use of these systems. In addition to the provision of a sound foundation in traditional, second generation database systems, it explores the representation and management of complex information resources with third generation and NOSQL database technology. The module also highlights how database systems are at the core of modern information-rich Web sites, and explores the role of XML and “Web of data” technologies. Systems for data mining and business intelligence will be discussed.
 

1. Design a relational database, i.e. map conceptual models to efficient representations in a database schema.
2. Query a relational database.
3. Describe and Evaluate the principles of other types of database management systems – object-oriented, object-relational, NoSQL, cloud, distributed.
4. Discuss the principles of data mining algorithms and critically analyse their applications in business intelligence.
5. Describe how markup languages and Semantic Web technologies are used to model and manage information in a Web context.

This module will be delivered through a combination of lectures, supervised lab sessions, example classes and tutorials, as appropriate.

 

Be able to understand the role of information in decision making.

Be able to define and contrast the terms: data, information and knowledge.

Be able to design a relational database including:

  (1) conceptual design (build a model independent of the choice of a database management system)

  (2) logical design (create the database in a chosen database management system)

  (3) physical design (physically store the database on disk)

Be able to understand issues concerning database applications including database security and data integrity.

Be able to access relational databases from computer programs.

Be able to use markup languages (XML and JSON) and Semantic Web to model information.

Be able to design and query object-oriented and object-relational databases.

Be able to understand the difference between relational and NoSQL databases.

Be able to select appropriate techniques for mining large data sets.

Be able to identify ways in which systems can be designed to support business operations by providing business intelligence.

Coursework will consist of a series of problem solving questions that address learning outcomes LO1 and LO2. The relevant topics from the syllabus include:

Introduction to databases

  Information, data and knowledge

  Database systems

  Relational data model

  SQL

  Relational algebra

Database design

  Conceptual database design (ER diagrams)

  Logical database design (ER to SQL)

  Physical database design (indexes)

Problem solving questions may include but would not be limited to examples such as writing SQL queries, designing a database using an ER diagram or normalizing a database.

The coursework will be set in Week 6 of the Spring semester. The coursework submission date will be during Week 11 of the Spring semester.

NOTE: The exam will also be covering the learning outcomes LO1 and LO2, but it will be focusing on different topics. Some topics from the part of the syllabus covered by the coursework will be relevant for the exam as well, but the exam will be focusing largely on this part of the syllabus in relation to the learning outcomes LO1 and LO2:

Security, transactions and concurrency

  Security and integrity

  Transactions and recovery

  Concurrency control

The exam will also contain questions that will test the learning outcomes LO3, LO4 and LO5, which will be covered by the remainder of the syllabus.

Students will be provided with reassessment opportunities in line with University regulations.

Introduction to databases

  Information, data and knowledge

  Database systems

  Relational data model

  SQL

  Relational algebra

Database design

  Conceptual database design (ER diagrams)

  Logical database design (ER to SQL)

  Physical database design (indexes)

Security, transactions and concurrency

  Security and integrity

  Transactions and recovery

  Concurrency control

Object orientation

  SQL and programming languages (Java)

  Object-oriented databases

  Object-relational databases

Markup languages and NoSQL databases

  XML, XPath and XQuery

  JSON

  NoSQL

Data mining

  Frequent itemsets

  Similarity and distance

  Clustering

  Classification

Semantic Web

  URI, RDF

  Ontologies