Module overview
This module is intended to provide you with a blend of theory and current practice in organisational decision making and data management. The module critically discusses the complexity of organisational decision making by identifying key concepts and relevant theories. The module examines the role of knowledge in the contemporary organisations and explore the ways it can be used for better data management. Existing models for analysing decision making processes are examined, as well as how information systems and analytical tools can be used to tap into (big) data and support and enhance decision making within different organisational contexts.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Recommend appropriate proposals for digital decision support systems in organisations.
- Assess decision support requirements in organisations.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Effectively use a data analysis tool.
- Collaborate in groups to solve data related problems.
- Develop detailed reports of appropriate complexity for a given audience.
- Communicate data analysis results in a meaningful way.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- The role of knowledge in decision making in organisations.
- The capabilities and limitations of information systems in supporting decisions.
- The theory and practice of decision support and analysis.
Syllabus
- Fundamental of organisational decision making, qualitative complexity, and implication of information systems
- Fundamentals of business intelligence, data warehousing, data mining and big data
- Fundamentals of knowledge and knowledge management
- Decision making and modelling approaches
- Codification of knowledge and expert systems
- Group decision support systems
Learning and Teaching
Teaching and learning methods
The module consists of seminars, case studies, demonstrations and practical sessions (computer laboratory sessions) as well as guest lectures from the leading experts from the industry. Computer facilities will be booked for use by this module.
Type | Hours |
---|---|
Teaching | 24 |
Independent ÃÛÌÒTV | 126 |
Total study time | 150 |
Resources & Reading list
Textbooks
Sharda, R., Delen, D. and Turban, E. (2014). Business Intelligence and Analytics: Systems for Decision Support. Pearson.
Papathanasiou, J., Ploskas, N. and Linden, I. eds. (2016). Real-World Decision Support Systems: Case Studies (Vol. 37). Springer.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Questions and answers
- Assessment Type: Formative
- Feedback: - In-lecture review questions/problems. - Response to students' questions during lectures, classes or through other means (e.g. email and Blackboard-Discussion Board).
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Coursework | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Coursework | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
Method | Percentage contribution |
---|---|
Coursework | 100% |
Repeat Information
Repeat type: Internal & External