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Course module: JM0100-M-6
JM0100-M-6
Business Analytics
Course info
Course moduleJM0100-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Economics and Management; TiSEM: Econometrics and OR; Econometrics & Operations;
Is part of
M Data Science and Entrepreneurship (joint degree)
Contact personprof. dr. G. Kant
Lecturer(s)
Lecturer
prof. dr. G. Kant
Other course modules lecturer
Starting block
C1
Course mode
Full-time
RemarksThis information is not up to date. Check the Course Catalog 2018 or select the course via “Register”.
Registration opennot known yet
Aims
After following this course, the students will be able to:

  • discuss the advantages of modern analytics for businesses;
  • understand the business analytics tools and techniques
  • apply meta-heuristics for optimization of operational processes
  • apply analytics for improved decision support (to problems in logistics, finance and marketing) and understand the ramifications of prescriptive analytics for delivering marketable products and solutions

Specifics

This course focuses in particular on prescriptive analytics, which focuses on what will happen and when and why. Moreover, it suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option. We will discuss optimization techniques to make better decisions supported by existing data.

The key course subjects include prescriptive analytics and optimization methods. We will work in teams on real-life case studies, like in logistics, economics, finance and marketing. The large case study at the end of this course will most likely be about dynamic pricing, like applied for flight, holiday and hotel bookings.

Data sets
The students will work in teams on real-life case studies using real world dataset in logistics, finance and marketing. The large case study at the end of this course will most likely be about dynamic pricing, like applied for flight, holiday and hotel bookings.

Content
The course is divided into four modules. Each module (appr. 4 weeks) consists of lectures and assignments (individual and/or in groups). Topics included in each module are:

Module 1: Introduction, predictive analytics versus prescriptive analytics, optimization methods (linear)
Module 2: Optimization methods (integer, robust), Meta-heuristics, applications in logistics, finance
Module 3: Applications in marketing, internet, health care, public organizations
Module 4: dynamic pricing and (group) project work, presentations

Type of instructions

Lectures, Lab sessions, Self-study, Group work (research, writing reports and giving presentations)

Type of exams

Assignments (60%) and written exam (40%)

Compulsory Reading
  1. Bertsimas, D., O'Hair, A., Pulleyblank, W., The Analytics Edge. Required papers and chapters will be uploaded unto Blackboard


Recommended Reading
  1. Recommended literature will be uploaded unto Blackboard.
Required materials
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Recommended materials
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