Data Analytics

Content

The discipline Data Analytics mainly emphasises ‘Business Intelligence’ and refers to the analysis of business data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better business decisions. McKinsey and Gartner claim that there is an enormous shortage of graduates in this field. Due to the more quantitative schooling of business engineers, emphasis is placed on price-fixing, analytical customer management systems (analytical Customer Relationship Management = aCRM), predictive and prescriptive analytics as well as more recent evolutions in Big Data, social media and web analysis.

Who are we

• Johan Verrue
• Ramon Ganigué
• Dirk Buyens
• Mia Loccufier
• Steve Muylle
• Paul Gemmel
• Geert Poels
• Katrien Verleye
• Frederik Gailly
• Miguel Meuleman
• Matthias Bogaert
• Dirk Van den Poel
• Dries Benoit
• Broos Maenhout

Courses related to this subject

Students are required to follow all courses from the list mentioned below.

More information (content, teaching methods, etc.) can be found in the study guide.

• Social Media and Web Analysis
• Analytical Customer Relationship Management
• Machine Learning
• Simulation Modelling and Analysis
• Predictive and Prescriptive Analytics
• Big Data

3 reasons to choose data analytics

1. Interdisciplinary program (engineering, entrepreneurship, technology, IT, business economics) with focus on business analytics
2. Balance between fundamental theory and case studies in data analytics (hands-on teaching)
3. View on the newest techniques and software to analyse data