INFO2048-1 : Business Analytics

Study Programmes 2015-2016

INFO2048-1

Business Analytics

Duration :

30h Th

Number of credits :

Master in business engineering (120 ECTS)		5

Lecturer :

Michael Schyns

Language(s) of instruction :

English language

Organisation and examination :

Teaching in the second semester

Units courses prerequisite and corequisite :

Prerequisite or corequisite units are presented within each program

Course contents :

No company can survive without a good management information system. Nowadays, a company must be able to collect, analyze and handle huge volume of data in order to answer managerial questions and/or offer new top value services. Amazon, Google, Facebook are obvious successful stories confirming the importance of data management.
Three keywords to define the course:

Management field: Decision Making
Approach: Data analysis (Analytics)
Theory (basics) and applications

In this course, the main question is: How to transform raw "stupid" data into valuable "actionable" information? Common applications in finance are fraud detection, credit risk analysis, risk profile, pricing... Common applications in eCommerce are recommendation tools, converting clicks into customers... Other common applications in Supply Chain Management are revenue management (e.g. airline ticketing), capacity management, diagnosis of production faults, forecasting demand, predictive modeling, advanced reporting based on ERP systems... Common applications in marketing and sales are the analysis of customer loyalty, the analysis of the market basket, the identification of prospective customers)...
This course covers techniques such as:

advanced reporting with Excel (DB functions, filters, pivot table...)
reporting with advanced visual tools like "Tableau"
data mining tools: - data preparation - decision trees - neural networks - linear and logistic regression - market basket analysis (with Java exportation for e-commerce) - clustering - model analysis

Learning outcomes of the course :

Gaining the knowledge and understanding of the chosen concentration field.
Understanding and being able of using modelization methods.
Capacity to research autonomously and methodically the information needed to solve a complex, transversal management problem.
Integrate autonomously researched information, tools, knowledge and context to build and propose original, creative and viable solutions to concrete complex management problems whether real or simulated.
Providing concrete solutions to a management problem, integrating modelization methods and/or a dimension of technology, innovation or production.
Developing a critical sense (arguing).
Professional capacity for written communication.

Prerequisite knowledge and skills :

Basic computer skills Basic programming skills (html and PhP/Java) Basic statistical knowledge

Planned learning activities and teaching methods :

Theory is immediately illustrated by small examples. Students perform exercises on computer during the lectures. Real cases are considered (e.g. revenue management, bankruptcy detection, customer choice...)
They will acquire a basic theoretical knowledge but also learn to use professional tools like Excel for basic reporting, Tableau for advanced visual reporting, SAS Enterprise Miner (datamining).
The students have also to develop an e-commerce website with recommendation tools (group project)

Mode of delivery (face-to-face ; distance-learning) :

All lectures are given in a computer room.