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Course module: 320091-M-6
320091-M-6
Business Analytics and Emerging Trends
Course info
Course module320091-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Economics and Management; TiSEM: Management; TiSEM: Management;
Is part of
M Marketing Analytics
M Communication and Information Sciences
M Information Management
M Supply Chain Management
M Data Science and Society
Contact persondr. H. Weigand
Lecturer(s)
Lecturer
dr. S. Angelopoulos
Other course modules lecturer
Lecturer
prof.dr.ir. H.A.M. Daniels
Other course modules lecturer
Coordinator course
dr. H. Weigand
Other course modules lecturer
Starting block
BLOK 2
Course mode
Full-time
RemarksThis information is not up to date. Check the Course Catalog 2019 or select the course via “Register”.
Registration openfrom 19/10/2018 09:00 up to and including 31/07/2019
Aims
With the digitalization of enterprise information systems, the proliferation of internet and the widespread use of mobile devices and sensor technology, the amount of data stored in systems has grown enormously. Simultaneously, high speed CPU and fast massive memory enable new business analytics, like web analytics, text mining and social network analysis.
After completing this course, you will be able to:
  • Explain the main trends in business analytics;
  • Assess new IT developments from a business value perspective;
  • Calculate the value of information (the information gain) in simple cases.
Content
The course consists of lectures, lab sessions, guest lectures and a group paper assignment. Topics covered in the lectures include:
  • Creating value with big data;
  • Information theory;
  • Text mining, social network analysis;
  • Smart auditing, process mining;
  • High-performance data processing;
  • Responsible data science
For each lecture, you have to read some scientific articles or other background material. The lab part is mainly by self-study and introduces you to process mining and to the programming language Python (not for students Data Science & Society). In addition, guest lectures will provide insight in practical applications in e.g. auditing, marketing and logistics. Students from Data Science & Society have to write a group paper that gives a critical evaluation of the application of business analytics in some business domain.
Type of instructions
Lectures, self-study, lab sessions and guest lectures
Type of exams
Written exam (80%) and assignment: Group paper (DS&S) OR Python lab (20%),
Specifics
The result of the assignment is not transferable to the next year.
Students are expected to have a basic level of Statistics, or to acquire that with selfstudy in the first weeks.


 
Timetable information
320091-M-6|Business Analytics and Emerging Trends
Written test opportunities
Omschrijving/DescriptionToets/TestBlok/BlockGelegenheid/OpportunityDatum/Date
Written test opportunities (HIST)
Omschrijving/DescriptionToets/TestBlok/BlockGelegenheid/OpportunityDatum/Date
Exam / ExamOTH_01BLOK 2121-12-2018
Exam / ExamOTH_01BLOK 2222-01-2019
Required materials
List of literature
Verhoef, P.C., Kooge, E. & N. Walk, Creating Value with Big Data Analytics making smarter marketing Decisions, Routledge, 2016. ISBN-13 978-1138837973, ISBN-10 1138837970
Title:Creating Value with Big Data Analytics making smarter marketing Decisions,
Author:Verhoef, P.C., Kooge, E. & N. Walk
Publisher:Routledge
Articles
Scientific articles to be announced.
Recommended materials
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Tests
Exam

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