The module will focus on analytic skills that are required to support the following areas:-

Data Mining and Decision Support Systems -
topics to include (not exhaustive):
Analytics of data derived from data warehousing and data mining
concepts, techniques, related disciplines (e.g. OLAP etc.), classification, clustering, data marts, dashboards, Text Mining etc

Data Warehousing - architecture, star scheme, tuning, ETL, etc.
Performance issues loading, querying etc.
NoSQL and Big Data including cloud data concepts and virtualization

An assignment including a proof of concept artefact supported by a report 100%
Assessing all Learning Outcomes
Recommended word count is 3000

Knowledge Management in Theory and Practice (2nd Edition),Dalkir, Kimiz, 2011, MIT Press, 9780262295383

Knowledge Management Analysis, Design and Implementation, Cheema, D.S. 2010,Abhishek Publications , 9789350434260

Case study material and practical workbooks will be provided when appropriate to the schedule.
Lecture notes and guided reading will be provided electronically prior to delivery and be available throughout the running of the course.
Any suitable database management software and any suitable data modelling software.

None

Research led teaching approach which will include presentations by research students and/or others involved in the field.

The module will be delivered through the means of keynote lectures based on the core material, which will be reinforced by the use of tutorials and discussion groups to illustrate the main points through the application of theories and techniques to small case studies.