Overview:
- Credits:
- 10.0
- Level:
- 4
- Semester:
- Summer
- Subject:
- Marketing
- School:
- Business
- Coordinator:
- Dr Daniel Knapp
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Curricular information is subject to change
Learning Objectives
• Learn about the sources, types and quality of big data
• Understand the necessary infrastructural investments to harness and cleans big data
• Comprehend core analytical techniques and tools to generate insight from data
• Learn about new industry players and dash-board solutions
• Learn how to effectively summarise, visualise and communicate insights generated from big data.
• Understand the ethical and regulatory dimensions of customer data
Student Effort Type | Hours |
---|---|
Lectures | 0 |
Total | 0 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Essay: 1,000 word essay based on 1 of 3 questions | Coursework (End of Trimester) | n/a | Standard conversion grade scale 40% | Yes | 50 |
Group Project: Group work on 1 of 3 case studies (each group can choose one) to bring the data science process to life. | Throughout the Trimester | n/a | Standard conversion grade scale 40% | Yes | 50 |
Not yet recorded |
• Group/class feedback, post-assessment
Individual component (1,000 word essay): 60% Group component (in-class group research and presentation): 40%
Name | Role |
---|---|
Dr Daniel Knapp | Lecturer / Co-Lecturer |
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