Courses Master Display 2020-2021

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
2 26-10-2020 11-12-2020 X X
5 12-4-2021 28-5-2021 X X
Level Advanced
Coordinator Burak Can
For more information: b.can@maastrichtuniversity.nl
Language of instruction English
Goals
This course aims at getting hands-on experience in analysing managerial decision processes based on available data from real-life cases.
Description
PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. THE INFORMATION PROVIDED HERE IS BASED ON THE COURSE SETUP PRIOR TO THE CORONAVIRUS CRISIS. AS A CONSEQUENCE OF THE CRISIS, COURSE COORDINATORS MAY BE FORCED 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. PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. THE INFORMATION PROVIDED HERE IS BASED ON THE COURSE SETUP PRIOR TO THE CORONAVIRUS CRISIS. AS A CONSEQUENCE OF THE CRISIS, COURSE COORDINATORS MAY BE FORCED 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 treats the theory and practice of Business Intelligence. Tools for the analysis of data are discussed, as well as methods for discovering knowledge from information and using this knowledge for intelligent decision making.
Methods for the analysis of data are presented, from current data mining toolboxes. We study how (and how not) to build predictive models to extract information from large data bases and how to interpret the more efficiently and to develop new services for the organizations that provide the data.
The course consists of applying up-to-data data mining techniques on real-life problems. These techniques will be implemented with modern software tools (SAS, SPSS modeler, Tableau, WEKA, XLMiner). Cases are selected from the literature and our own research experience.

Literature
* Data Science for Business, What You Need to Know about Data Mining and Data-Analytic Thinking, by Foster Provost and Tom Fawcett, O' Reilly Media 2013, ISBN 978-1-4493-6132-7, EBook ISBN 978-1-4493-6131-0.
* Other materials, i.e. articles, will be made available through Student Portal.
Prerequisites
Basic statistics.
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 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)
Master Information and Network Economics Business Electives
SBE Exchange Master Master Exchange Courses
SBE Non Degree Courses Master Courses