Module Descriptors
DECISION AND DATA MANAGEMENT
COIS50550
Key Facts
Faculty of Computing, Engineering and Sciences
Level 5
15 credits
Contact
Leader: Euan Wilson
Email: E.D.Wilson@staffs.ac.uk
Hours of Study
Scheduled Learning and Teaching Activities: 4
Independent Study Hours: 146
Total Learning Hours: 150
Assessment
- COURSEWORK weighted at 100%
Module Details
Module Learning Strategies
This module is intended for work based learners, and the delivery approach will come from the planned integration of work-based skills and academic learning through work-based activities. Where possible the learning will take place in the workplace, using a combination of work activities, supported by private study, and using underpinning academic input provided by the University.
Where agreed, the University will deliver materials via VLE (e.g. Blackboard), Virtual classroom (e.g. DimDim), telephone conferencing and other appropriate technologies. There will be no specific requirement for students to attend the University whilst studying this module, but where appropriate, arrangements may be made for face to face meetings, or classroom based delivery.
Where agreed, the University will deliver materials via VLE (e.g. Blackboard), Virtual classroom (e.g. DimDim), telephone conferencing and other appropriate technologies. There will be no specific requirement for students to attend the University whilst studying this module, but where appropriate, arrangements may be made for face to face meetings, or classroom based delivery.
Module Indicative Content
The module will focus on the following areas:-
Data Mining and Decision Support Systems - topics to include (not exhaustive): concepts, techniques, related disciplines (e.g. OLAP etc.), classification, clustering, datamarts, dashboards
Data Warehousing - architecture, star scheme, tuning, ETL, etc.
Performance issues loading, querying etc.
Data Mining and Decision Support Systems - topics to include (not exhaustive): concepts, techniques, related disciplines (e.g. OLAP etc.), classification, clustering, datamarts, dashboards
Data Warehousing - architecture, star scheme, tuning, ETL, etc.
Performance issues loading, querying etc.
Module Additional Assessment Details
Coursework 100%
Assessing all Learning Outcomes
Recommended word count is 3000
Students will be asked to complete a work based project which has been approved by both the employer and the University. The student will receive support from both an academic supervisor and a work based mentor.
Assessing all Learning Outcomes
Recommended word count is 3000
Students will be asked to complete a work based project which has been approved by both the employer and the University. The student will receive support from both an academic supervisor and a work based mentor.
Module Resources
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.
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.
Module Special Admissions Requirements
Prior study of module Introduction to Databases CE02002-1 or equivalent
Only avaialable for students on FCET Negotiated Undergraduate awards
Only avaialable for students on FCET Negotiated Undergraduate awards
Module Texts
Data Mining - Introductory and Advanced Topics, Dunham, 2002, Prentice Hall, ISBN 0-13-088892-3
Oracle DBA Guide to Data Warehousing and Star Schemas- Scalzo, 2003, Prentice Hall, ISBN 0-13-032584-8
Oracle DBA Guide to Data Warehousing and Star Schemas- Scalzo, 2003, Prentice Hall, ISBN 0-13-032584-8