Short Title:Data Warehousing and Business Intelligence
Full Title:Data Warehousing and Business Intelligence Systems
Language of Instruction:English
Module Code:DATA H2000
  
Credits: 5
Field of Study:Marketing and advertising
Module Delivered in 4 programme(s)
Reviewed By:GLENN MEHTA
Module Author:GARRY O REGAN
Module Description:The purpose of this module is: 1.To inform students to the potential of data warehousing and business intelligence (BI) systems, including online data analysis and data mining, in a marketing environment; 2.To enable students to identify the implications of different database design approaches on the effectiveness of data warehousing/BI applications; 3. To produce students capable of applying data warehousing and data analysis/data mining techniques in an effective and result-oriented manner in a corporate environment.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Describe the features and capabilities of data warehousing, for supporting data analysis.
LO2 Assess the suitability of different database design approaches to the needs of data warehousing/BI applications, and demonstrate an ability to apply appropriate design techniques.
LO3 Explain the processes involved in transferring data from source business databases into a data warehouse, including the resolution of data quality issues.
LO4 Describe the different types of business intelligence tools available to perform online analysis against corporate data warehouses (and sub-sets), and demonstrate an ability to apply a selection of these tools.
LO5 Explain the nature of data mining, and identify the potential of various data mining tools and techniques to support market-related analysis of corporate data.
 

Module Content & Assessment

Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Continuous Assessment In-lab assessment: the student will demonstrate the ability to extract data from a standard business database, transform it as appropriate and transfer it into a database format suitable to data warehousing. The assessment includes the design of the target database according to principles covered in class. 2,3,4 20.00 Week 6
Continuous Assessment In-lab assessment: the student will demonstrate his/her ability to perform specific data analysis and data mining activities against data extracted from a data warehouse. 4,5 20.00 Week 11
Continuous Assessment Work submitted weekly at each lab is marked, to encourage ongoing student engagement. A reasonable effort is expected for each submission, for marks to be awarded. 2,4 10.00 Ongoing
Multiple Choice Questions Online theory quizzes will be used at intervals during the semester to provide formative feedback to the student on his/her learning to date. 1,2,3,4,5 10.00 n/a
End of Module Formal Examination
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formal Exam End-of-Semester Final Examination 1,2,3,4,5 40.00 End-of-Semester

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
Lecture Instruction on theoretical underpinnings of the module 1.00 Every Week 1.00
Lab Instruction, and practical application of learning, to create a data warehouse, and perform data mining 2.00 Every Week 2.00
Independent Learning Time Reading/Study/Practicing of practical skills 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
Lecturer/Lab Instruction on theoretical underpinnings of the module; Instruction, and practical application of learning, to create a data warehouse, and perform data mining. 2.00 Every Week 2.00
Independent Learning Time reading/study/practising of practical skills 7.00 Every Week 7.00
Total Weekly Learner Workload 9.00
Total Weekly Contact Hours 2.00
 

Module Resources

Recommended Book Resources
  • Ralph Kimball [and four others]. 2015, The Kimball Group reader, 2nd Edition Ed., New York; Wiley [ISBN: 1119216311]
  • Ralph Kimball, Margy Ross. 2013, The data warehouse toolkit, 3rd Ed. Ed., New York; John Wiley & Sons, Inc [ISBN: 1118530802]
  • Joy Mundy, Warren Thornthwaite, Ralph Kimball (Contributor) 2011, The Microsoft Data Warehouse Toolkit, 2nd ed. Ed., Wiley [ISBN: 978-0470640388]
  • Christopher Adamson 2010, The complete reference star schema, First edition Ed., McGraw-Hill New York [ISBN: 978-0071744324]
  • Matteo Golfarelli, Stefano Rizzi; translated by Claudio Pagliarani 2009, Data warehouse design, First edition Ed., McGraw-Hill New York [ISBN: 978-0071610391]
  • Thomas C. Hammergren, 2009, Data Warehousing For Dummies, 2nd ed. Ed., For Dummies [ISBN: 978-0470407479]
This module does not have any article/paper resources
This module does not have any other resources
 

Module Delivered in

Programme Code Programme Semester Delivery
TA_BAMCO_B Bachelor of Arts (Honours) in Advertising & Marketing Communications 4 Mandatory
TA_BADMT_B Bachelor of Arts (Honours) in Digital Marketing Technologies 4 Mandatory
TA_BAMCO_D Bachelor of Arts in Advertising and Marketing Communications 4 Mandatory
TA_BMKDM_D Bachelor of Arts in Digital Marketing 4 Mandatory