Courses NonDegree Display 2022-2023

Course Description To PDF
Course title Business Intelligence Case Studies
Course code EBC4107
ECTS credits 6,5
Assessment Whole/Half Grades
Period
Period Start End Mon Tue Wed Thu Fri
5 17-4-2023 9-6-2023 X X
Level Advanced
Coordinator Roberto Cerina
For more information: r.cerina@maastrichtuniversity.nl
Language of instruction English
Goals
This course aims at providing students with tools and experience to analyse real-life data for a real-time, sensitive business intelligence case-study.
Description
PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. A RE-EMERGENCE OF THE CORONAVIRUS AND NEW COUNTERMEASURES BY THE DUTCH GOVERNMENT MIGHT FORCE COORDINATORS TO CHANGE THE TEACHING AND ASSESSMENT METHODS USED. THE MOST UP-TO-DATE INFORMATION ABOUT THE TEACHING/ASSESSMENT METHOD(S) WILL BE AVAILABLE IN THE COURSE SYLLABUS.

This course is highly technical, and treats the practical aspects of producing real-life Business Intelligence, as well as covering the computational tools to implement this. Tools for the analysis of data are discussed, focusing on tools which emphasise the importance of uncertainty in intelligent decision-making.
We study how (and how not) to build predictive models to frequently extract information from dynamic data, and how to interpret these methods and summaries intuitively and efficiently develop new services for the organisations that provide the data.
These techniques will be implemented with the R open-source software. Cases are selected from the literature and our own research experience.
Literature
* Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan.
* https://mc-stan.org/users/documentation/
* Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis. CRC Press.
* Other materials will be made available through Student Portal.
Prerequisites
Basic Statistics, Regression, Basic R
Teaching methods (indicative; course manual is definitive) PBL / Presentation / Lecture / Assignment / Groupwork
Assessment methods (indicative; course manual is definitive) Final Paper / Participation / Presentation
Evaluation in previous academic year For the complete evaluation of this course please click "here"
This course belongs to the following programmes / specialisations
Master Business Research - No specialisation Year 1 Disc - IB Inf Mgmt Bus Int
Master Business Research - Operations Research Year 1 Elective Course(s)
Master Business Research - Operations Research Year 2 Elective Course(s)
Master Digital Business and Economics Elective Course(s)
Master Human Decision Science Elective Course(s)
Master International Business - Accounting and Business Information Technology Elective Course(s)
Master International Business - Entrepreneurship and Business Development Elective Course(s)
Master International Business - Managerial Decision-Making and Control Elective Course(s)
Master International Business - Information Management and Business Intelligence Compulsory Course(s)
Master International Business - Marketing-Finance Elective Course(s)
Master International Business - Organisation: Management, Change and Consultancy Elective Course(s)
Master International Business - Strategic Corporate Finance Elective Course(s)
Master International Business - Strategic Marketing Elective Course(s)
Master International Business - Strategy and Innovation Elective Course(s)
Master International Business - Supply Chain Management Elective Course(s)
Master International Business - Sustainable Finance Elective Course(s)
SBE Exchange Master Master Exchange Courses
SBE Non Degree Courses Master Courses