Short Title:Advanced Data Analysis and Modelling
Full Title:Advanced Data Analysis and Modelling
Language of Instruction:English
Module Code:INCD H4000
 
Credits: 5
Field of Study:Marketing and advertising
Module Delivered in 3 programme(s)
Reviewed By:GLENN MEHTA
Module Author:Deryck Payne
Module Description:The aim of this module is twofold: 1. to provide the learner with an understanding of the application of the procedures and tools used for measuring digital campaigns, along with practical reporting of digital campaign measurement, and 2. to build on previous learning in the area of data mining, and explore the potential of data analytics in a marketing and advertising context.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Apply a range of specialised data analysis techniques and tools in a Marketing and Advertising context.
LO2 Identify the potential of data analytics tools for Marketing and Advertising.
LO3 Compare and critically assess the features of data analytics tools available to Marketing and Advertising professionals.
LO4 To make effective us of spreadsheet business and statistical functions, IF statements, sensitivity analysis, pivot tables, advanced charting, and spreadsheet data tools.
LO5 Create meaningful, business related, dashboards and reports.
 

Module Content & Assessment

Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Continuous Assessment Spreadsheet Skills: Weekly individual assignments, based on the weeklynlab sessions, to be completed by the following session. 4,5 10.00 Ongoing
Laboratory Dashboards and Reporting: Two formal in-class tests in which the student will complete an assignment in the lab to test the achievement of learning outcomes for the practical work to date. 4,5 40.00 Ongoing
Continuous Assessment Data Analytics - weekly individual and group assignments: in addition to the formal test points, Marks will be awarded for regular individual and group assignments undertaken during weekly lab sessions (some of which may require completion by subsequent session) 1,2,3 25.00 Ongoing
Laboratory Data Analytics - practical work assessment: a formal in class test in which the student will complete an assignment in-class, to test the achievement of learning outcomes for the practical work to-date. 1 25.00 Sem 1 End
No End of Module Formal Examination

TU Dublin – Tallaght Campus reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lab A mixture of theory and practical/ exploratory tuition in a lab environment 3.00 Every Week 3.00
Independent Learning Review and practice of material covered in the lab class. 6.00 Every Week 6.00
Total Weekly Learner Workload 9.00
Total Weekly Contact Hours 3.00
Workload: Part Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lab A mixture of theory and practical/ exploratory tuition in a lab environment 2.00 Every Week 2.00
Independent Learning Review and practice of material covered in the lab class. 7.00 Every Week 7.00
Total Weekly Learner Workload 9.00
Total Weekly Contact Hours 2.00
 

Module Resources

Recommended Book Resources
  • Ignatow, Gabe and Rada, Mihalcea 2016, Text Mining: A Guidebook for the Social Sciences, 1st Ed Ed., Sage [ISBN: 148336934X]
  • Siegel, Eric and Davenport, Thomas H. 2016, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Ed. 2 Ed., Wiley [ISBN: 1119145678]
  • Larose, Daniel 2014, Discovering Knowledge in Data, Ed.2 Ed., Wiley
  • Provost, Foster and Fawcett, Tom 2013, Data Science for Business: What you need to know about data mining and data-analytic thinking, Ed. 1 Ed., O'Reilly Media
  • Bill Jelen ,‎ Michael Alexander 2016, Pivot Table Data Crunching, 1 Ed., New York; Wiley [ISBN: 0789756293]
Recommended Article/Paper Resources
  • Wiley Periodicals, Inc Journal of Interactive Marketing
Other Resources
  • Online Download: Megaputer Intelligence Inc. 2017, Polyanalyst 6 Hands-On Tutorial, Illinois, U.S.
 

Module Delivered in

Programme Code Programme Semester Delivery
TA_BAMCO_B Bachelor of Arts (Honours) in Advertising & Marketing Communications 7 Mandatory
TA_BADMT_B Bachelor of Arts (Honours) in Digital Marketing Technologies 7 Mandatory
TA_BMDMT_B Bachelor of Arts (Honours) in Digital Marketing Technologies 7 Mandatory