The module offers hands-on practical real world applications and the opportunity to work with real-world software relevant to Big Data Analytics
Big Data in action and how different organisations are using big data in fields such as banking, travel, telecoms, genetics, IOT, to mention but few.

Related topics to cover professional issues and project management methods.

Weighted at 40% Presentation: 15 minutes which discusses the choice of data sets and its characteristics, and how these impacted the approach and tools to analytics and representation. All illustrated by the undertaken project. Learning outcomes 1 and 2.

Weighted at 60% 1800 word Report: is more an executive report, emulating a real case scenario where you are in a work place and you are given a small big-data analytics projects and you are required to right an executive report to explain the problem, its characteristics and how it has been approached and the presentation of the results with insights from the analysis.
Learning outcomes 1, 2 and 3.

The VLE will provide supporting learning materials. The module will use a discussion forum and blog posts to allow students to share ideas and expertise. Tutor support will be available via the discussion forum and Skype and also by email and telephone.

Hurwitz 2013 Big Data for Dummies Wiley and Sons

NoSQL Datastores (MongoDB, CouchDB)
Hadoop Framework
Facilities for Distributed systems for parallel processing.
IBM SPSS

1) Critically discuss and evaluate domain-specific techniques for applying Big Data Analytics to different domains. (Knowledge and Understanding, Enquiry).
2) Research, analyse and critically evaluate best practices in big data analytics and ability to extract value and insight from data through practical work. (Enquiry, Analysis).
3) Test and develop systematic analytical approaches to problem solving and ability to present logical and coherent written arguments for choice of approach. (Enquiry, Analysis, Communication).