Module Descriptors
OPERATIONAL AND ANALYTICAL DATABASES
COIS71032
Key Facts
Digital, Technology, Innovation and Business
Level 7
15 credits
Contact
Leader: Edmund Dudley
Email: Carl.Dudley@staffs.ac.uk
Hours of Study
Scheduled Learning and Teaching Activities: 36
Independent Study Hours: 114
Total Learning Hours: 150
Assessment
- ASSIGNMENT weighted at 100%
Module Details
Module Indicative Content
Quality and Integrity of Data
Data Mining - topics include (not exhaustive): concepts, techniques, related disciplines (e.g. OLAP etc), classification, clustering, Web, spatial and temporal mining.
Data Warehousing - architecture, star schema, tuning, loading, etc.
Dimensional modelling
Customer Relationship Management - overview of, ECRM, MCRM etc. and Decision support systems
Web, Mobile and roaming databases: issues and technologies related to database technology
Data and database security
Data Mining - topics include (not exhaustive): concepts, techniques, related disciplines (e.g. OLAP etc), classification, clustering, Web, spatial and temporal mining.
Data Warehousing - architecture, star schema, tuning, loading, etc.
Dimensional modelling
Customer Relationship Management - overview of, ECRM, MCRM etc. and Decision support systems
Web, Mobile and roaming databases: issues and technologies related to database technology
Data and database security
Module Additional Assessment Details
Individual Research Paper (100%) (3,000 words) assessing Learning Outcomes 1 to3
comprising:
a) Conference style presentation of research findings and evaluation (20%)
b) A detailed research paper styled as a journal publication. (80%)
comprising:
a) Conference style presentation of research findings and evaluation (20%)
b) A detailed research paper styled as a journal publication. (80%)
Module Learning Strategies
18 lectures, 18 seminars
Students will have participated in an award induction workshop where they will learn how to use the Virtual Learning Environment (VLE) employed for the study of this module. Subsequently students will work through the module material provided on the VLE at a pace suggested within the VLE for the module. The material will include activities and review questions that allow students to assimilate the concepts and skills required by the module. Students will be encouraged to discuss relevant aspects within discussion forums that are part of the VLE. The forums will allow discussion with a student's peer group as well as the module tutor.
Students will have participated in an award induction workshop where they will learn how to use the Virtual Learning Environment (VLE) employed for the study of this module. Subsequently students will work through the module material provided on the VLE at a pace suggested within the VLE for the module. The material will include activities and review questions that allow students to assimilate the concepts and skills required by the module. Students will be encouraged to discuss relevant aspects within discussion forums that are part of the VLE. The forums will allow discussion with a student's peer group as well as the module tutor.
Module Resources
None
Module Special Admissions Requirements
None
Module Texts
Discovering Knowledge in Data: An Introduction to Data Mining, Daniel T. Larose, 2013, Wiley-Blackwell; ISBN: 0470908742
Practical Data Mining for Business - Case Studies and Methodology Andrea Ahlemeyer-Stubbe; Shirley Coleman, 2013, Wiley-Blackwell ISBN: 1119977134
Database Systems: A Practical Approach to design, Implementation and Management, Connolly, Begg, Addison Wesley, 5 edition (16 April 2009), ISBN-10: 0321523067
Practical Data Mining for Business - Case Studies and Methodology Andrea Ahlemeyer-Stubbe; Shirley Coleman, 2013, Wiley-Blackwell ISBN: 1119977134
Database Systems: A Practical Approach to design, Implementation and Management, Connolly, Begg, Addison Wesley, 5 edition (16 April 2009), ISBN-10: 0321523067