CS988 - Big Data Tools and Techniques

Credits

Level

Semester

Semester 1

Availability

Possible elective

Prerequisites

N/A

Learning Activities Breakdown

Lectures: 10 | Labs: 10
Homework / Private Study: 80

Items of Assessment

Assessment

Exam

Lecturer

William Bell

The aim of this module is to endow students with:

an understanding of the new challenges posed by the advent for big data, as they refer to its modelling, storage, and access;
an exposure to a number of different big data technologies and techniques, to show how they can achieve efficiency and scalability while also addressing design trade-offs and their impacts.

After completing this module participants will be:

familiar with a number of different cloud NoSQL systems and their design and implementation, showing how they can achieve efficiency and scalability while also addressing design trade-offs and their impacts;
familiar with the Map-Reduce programming paradigm.

Overview of various NoSQL cloud storage systems such as document stores like MongoDB, column stores like Cassandra and graph databases like Neo4j;
Distributed data processing with Hadoop and MapReduce.

Syllabuses - PG