Teaching Responsibility
LJMU Schools involved in Delivery:
Computer Science and Mathematics
Learning Methods
Lecture
Practical
Module Offerings
7012DATSCI-SEP-CTY
Aims
The module aims to develop skills in modern computing techniques for high performance analysis of large data sets and an understanding of how to translate an analysis problem to best exploit such techniques.
Learning Outcomes
1.
Analyse the unique features of Big Data analysis, its architectural components and the programming models used.
2.
Synthesize appropriate data models to suit the characteristics of the data
3.
Evaluate traditional and Big Data Management Systems and their different implementations.
4.
Synthesize the skills taught in the module in the context of creation of a big data information system.
Module Content
Outline Syllabus:1. The Big Data landscape including examples of real world big data problems
2. Architectural components and programming models used for scalable big data analysis
3. Hadoop and MapReduce
4. Suitable data models
5. Techniques to handle streaming data
6. Big Data Management System
7. Big Data Information System
Module Overview:
This module aims to develop skills in modern computing techniques for high performance analysis of large data sets. It also provides an understanding of how to translate an analysis problem to best exploit such techniques.
This module aims to develop skills in modern computing techniques for high performance analysis of large data sets. It also provides an understanding of how to translate an analysis problem to best exploit such techniques.