Aims and Fit of Module

• To introduce students to the fundamental algorithms on database indexing; • To introduce students to the fundamental algorithms and techniques on query processing and optimisation; • To introduce students to the problems arising from concurrency in databases, and how they are solved; • To introduce students to the problems arising from the integration of heterogeneous sources of information and the use of semi-structured data; • To introduce students to non-relational databases; • To introduce students to techniques for analysing large amounts of data

Learning outcomes

A. Demonstrate an understanding of advanced SQL topics on indexing, query processing and optimisation; B. Identify and apply the principles underpinning transaction management within relational DBMS; C. Illustrate the issues related to the recent Web technologies, semi-structured and structured data representation formalism; D. Identify the principles underlying object relational databases, distributed databases, big data storage systems and blockchain based storage systems; E. State the main concepts in data warehousing and data mining

Method of teaching and learning

Students will be expected to attend two hours of formal lectures as well as to participate in two hour of supervised lab session or tutorial in a typical week. In addition, students will be expected to devote eight hours of unsupervised time for reflection and consideration of lecture/tutorial/lab material and background reading