|Contact||Lectures: 10 | Labs: 10
Homework / Private Study
|Assessment||A 2-hour examination.|
|Lecturer||Dr Martin Halvey|
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, to enable students to write programs which can execute in massively parallel cloud-based infrastructures.
- 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.
* This list is indicative only – the class lecturer may recommend alternative reading material. Please do not purchase any of the reading material listed below until you have confirmed with the class lecturer that it will be used for this class.