Module Title:   Big Data Systems and Analytics

Module Credit:   20

Module Code:   CM-0438D

Academic Year:   2015/6

Teaching Period:   Semester 1

Module Occurrence:   A

Module Level:   FHEQ Level 7

Module Type:   Standard module

Provider:   Computer Science

Related Department/Subject Area:   School of Electrical Engineering & Computer Science

Principal Co-ordinator:   TBC

Additional Tutor(s):   TBC

Prerequisite(s):   None

Corequisite(s):   None

Aims:
To enable you to gain advanced knowledge and developed the skills on big data, concerning the architectures of big data systems, the management for big data project, and computational approaches for big data analytics.

Learning Teaching & Assessment Strategy:
A series of lectures will provide the essential theories and concepts. Laboratory sessions will provide you with opportunities to implement the systems architecture and test the difference of performance. Workshops will be organized for you to discuss and present your understanding on the selected topics. Oral feedback is given during the practical classes as appropriate. Module assessment consists of two coursework - one for individual work while another one for group work. The assessment is to test skills, knowledge and understanding for solving relevant practical problems on big data systems. The supplementary assessment follows the coursework format to address deficiencies encountered at the first attempt.

Lectures:   24.00          Directed Study:   146.00           
Seminars/Tutorials:   6.00          Other:   0.00           
Laboratory/Practical:   24.00          Formal Exams:   0.00          Total:   200.00

On successful completion of this module you will be able to...

demonstrate an advanced understanding and knowledge for the design of system architectures and data analytics approaches for big data projects.

On successful completion of this module you will be able to...

a) Design and implement suitable architectures for organizing and analyzing big data.
B) Demonstrate understanding of issues in big data project management.
C) Demonstrate skills and techniques for problem solving in big data analytics.

On successful completion of this module you will be able to...

Demonstrate effective communication, self-management and problem skills.

  Coursework   50%
 
  Coursework 1 (Group): Exercises on the design of system architectures.
  Coursework   50%
 
  Coursework 2 (Individual): Exercises on data analytics.
  Coursework   100%
 
  Supplementary coursework assessment (Individual)

Outline Syllabus:
1. Introduction to a variety of Systems Architectures for big data, study on different architectures and the associated functions.
2. The design of big data system to enable the effective analytics of big data.
3. Study a variety of approaches for big data analytics.
4. Study on a variety of cases on big data product design and innovation.
5. Study on a variety of applications of big data analytics in different domains.

Reading List
[1] Viktor Mayer-Schonberger, Kenneth Cukier, Big Data: A Revolution That Will Transform How We Live, Work and Think, Published by John Murray, 2013, ISBN: 1848547927
[2] Foster Provost and Tom Fawcett, Data Science for Business: What you need to know about data mining and data-analytic thinking. Published by O`Reilly, 2013. ISBN: 1449361323.
[3] Michael Minelli, Michele Chambers, and Ambiga Dhiraj, Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today`s Businesses (Wiley CIO), ISBN: 978-1-118-14760-3.

Version No:  1