IB3K5-12 Artificial Intelligence for Business
Introductory description
N/A.
Module aims
By providing understanding/insight for decision-making via access to structured data & knowledge assets across the enterprise as well as unstructured data throughout the internet and sensory technologies, data analytics enables an organisation to sense & respond to the demands of its operating environment.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Strategic nature and application of business intelligence practices and enterprise data management technologies in
contemporary organisations.
Management of data warehousing and business intelligence practices.
Business Analytics applications and tools.
Business intelligence practices: knowledge management, customer relationship mgt. and supply chain management
(CRM/SCM), business performance management, data mining.
Challenges in enterprise data/knowledge management: the case of dashboard.
Learning outcomes
By the end of the module, students should be able to:
- Understand the strategic nature of enterprise data knowledge management technologies and data analytics practices.
- Understand the strategic significance of the BI and Business Analytics systems, and the managerial issues associated with the selection and adoption of such data and manipulation technologies.
Indicative reading list
Davenport and Harris (2007). Competing on Analytics. HBR Press.
Sherman, R (2014) Business Intelligence Guidebook: From Data Integration to Analytics, Morgan Kaufmann.
Turban, E, Sharda, R, Delen, D. (2014) Business Intelligence and Analytics: Systems for Decision Support, Global Edition, Paperback. Pearson.
Turban, E., Sharda, R., Delen, D, & King, D (2011). 2nd ed. Business Intelligence: A Managerial Approach. Prentice Hall
Subject specific skills
Understand the managerial and organisational issues associated the use of data and business analytics systems and enterprise business intelligence practices.
Transferable skills
Know how to recommend management policies and measures to enable an organisation to exploit data/knowledge assets and information technologies effectively.
Study time
| Type | Required |
|---|---|
| Lectures | 10 sessions of 2 hours (17%) |
| Seminars | 9 sessions of 1 hour (8%) |
| Private study | 36 hours (30%) |
| Assessment | 55 hours (46%) |
| Total | 120 hours |
Private study description
Private Study.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group A1
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
Assessment component |
|||
| Individual Assignment (12 CATS) | 70% | 38 hours | Yes (extension) |
Reassessment component is the same |
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Assessment component |
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| Group Presentation (12 CATS) | 30% | 17 hours | No |
Reassessment component is the same |
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Feedback on assessment
Verbal and written.
There is currently no information about the courses for which this module is core or optional.