Module Descriptors
DATA WAREHOUSING AND DATA MINING
COIS51080
Key Facts
Digital, Technology, Innovation and Business
Level 5
15 credits
Contact
Leader: Russell Campion
Hours of Study
Scheduled Learning and Teaching Activities: 24
Independent Study Hours: 136
Total Learning Hours: 150
Assessment
  • INDIVIDUAL ESSAY (1500 WORDS) weighted at 100%
Module Details
ADDITIONAL ASSESSMENT DETAILS
COURSEWORK length 3000 WORDS weighted at 100%.
(Learning outcomes 1, 2 and 3)

Individual essay (1500 words) researching current issues concerning the use of data within organisations
INDICATIVE CONTENT
Overview of Data Warehousing principles and techniques:
Architectures, schemas, tuning, loading, etc.
Dimensional modelling
Data warehouse and database security
Overview of data mining principles and techniques:
Data Mining - topics include (not exhaustive): concepts, techniques, related disciplines (e.g. OLAP etc.), classification, clustering, web, spatial and temporal mining.
Handling missing data
Classification, link analysis/association, rule mining, clustering
Probabilistic and statistical methods
Genetic algorithms, neural networks
Data visualisation techniques
Data mining and knowledge discovery tools and applications
Data mining applications
Customer modelling/profiling, marketing, basket analysis etc.
RESOURCES
Data mining software: MATLAB, WEKA
SPECIAL ADMISSIONS REQUIREMENTS
NONE
TEXTS
Larose, D.T. (2013) Discovering Knowledge in Data: An Introduction to Data Mining, Wiley-Blackwell

Ahlemeyer-Stubbe, A. and Coleman, S. (2013) Practical Data Mining for Business - Case Studies and Methodology, Wiley-Blackwell
Christian, P. (2012) Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection. Springer
Witten, I.H., Frank, E. an Hall, M.A. (2011) Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann
Bishop, C. (2006) Pattern Recognition and Machine Learning, Springer
Science
Module Learning Strategies
"The learning strategy for the module includes 150 total learning hours, comprising:
- 13 hours of keynote lectures
- 13 hours of workshops/tutorials/discursive sessions
- 136 hours of independent, self-directed study

Keynote lectures introducing the main points for the topics covered by the core course material. Student-centred workshops/tutorials will develop and underline the main topics introduced in the lectures and
discussion sessions drawing on practical examples. Students will be encouraged to develop their intellectual, communicative and problem solving skills.
"