Module Details
Module Code: |
BUSS H4710 |
Module Title:
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Data Analytics (Tourism and Event Management)
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Title:
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Data Analytics (Tourism and Event Management)
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Module Level:: |
8 |
Module Coordinator: |
Janette Davies
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Module Author:: |
Edel Glowatz
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Module Description: |
The aim of this module is to provide students with an understanding of data analytics and to critically evaluate, select and utilise data analytics (including statistics) and the insights garnered ethically in a tourism & event management context
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Learning Outcomes |
On successful completion of this module the learner will be able to: |
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Learning Outcome Description |
LO1 |
Critically reflect on, evaluate and communicate the key principles, theories and techniques for data analytics as they apply the tourism and event management sectors |
LO2 |
Demonstrate practical knowledge of Web Analytics tools, Social Media Analytics and Email marketing Analytics |
LO3 |
Appraise and evaluate key business and marketing metrics, KPIs and customer segmentation |
LO4 |
Appraise and analyse data, present and defend it effectively to others |
Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is recommended before enrolment in this module.
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No recommendations listed |
Co-requisite Modules
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No Co-requisite modules listed |
Additional Requisite Information
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No Co Requisites listed
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Indicative Content |
Concept & current state of data analytics
Evolution & current status of data analytics, business & marketing insights
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Types of data (big data, structured, un-structured)
Evaluation of the types of data
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Digital marketing metrics and KPIs
Key marketing and business metrics & KPIs
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Marketing analytics techniques & tools (e.g.web & social media)
Web analytics (such as google analytics, heat mapping...)
Social media analytics (such as facebook insights, Twitter analytics)
email marketing analytics
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Data exploration
Data exploartion using pivot tables - exploration and visualisation of data
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Statistical analysis
Analysis of data using statistical techniques such as regression, correlation
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Customer segmentation
Segmenting customers and designing measureable marketing campaigns to target different segments
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Module Content & Assessment
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Assessment Breakdown | % |
Continuous Assessment | 100.00% |
AssessmentsFull Time
No End of Module Formal Examination |
Part Time
No End of Module Formal Examination |
Reassessment Requirement |
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
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SETU Carlow Campus reserves the right to alter the nature and timings of assessment
Module Workload
Workload: Full Time |
Workload Type |
Workload Category |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
Lecture |
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Contact |
Lectures |
12 Weeks per Stage |
3.00 |
36 |
Independent Learning Time |
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Non Contact |
Data Analytics |
15 Weeks per Stage |
5.93 |
89 |
Total Weekly Contact Hours |
3.00 |
Workload: Part Time |
Workload Type |
Workload Category |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
Lecture |
|
Contact |
Data Analytics |
12 Weeks per Stage |
1.50 |
18 |
Independent Learning Time |
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Non Contact |
Data Analytics |
15 Weeks per Stage |
2.97 |
44.5 |
Total Weekly Contact Hours |
1.50 |
Module Resources
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Recommended Book Resources |
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Sigala, M., Rahimi, R., Thelwall, M. (Eds.). (2019), Big Data and Innovation in Tourism, Travel, and Hospitality, Springer.
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Ćukasiewicz, K.. (2020), Big Data Analytics in Tourism, Taylor & Francis Group, [ISBN: 9781003057291].
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Wayne L. Winston. (2014), Marketing Analytics: Data-Driven Techniques with Microsoft Excel, John Wiley & Sons, p.720, [ISBN: 111841730].
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Rajkumar Venkatesan, Paul Farris, Ronald T. Wilcox. (2014), Cutting Edge Marketing Analytics: Real World Cases and Data Sets for Hands On Learning, Pearson Education, p.320, [ISBN: 0133552578].
| Supplementary Book Resources |
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Minelli, M., Smith, D., Chambers, M.. (2013), Big Data, Big Analytics - Emerging Business Intelligence and Analytic Trends for Today's Businesses, First. Wiley, p.256, [ISBN: 111814760X].
| Recommended Article/Paper Resources |
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Journal of Marketing Analytics.
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International Journal of Business
Analytics.
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Journal of Research in Interactive
Marketing.
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Journal of Service Research.
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MIT Sloan.
| This module does not have any other resources |
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