Data analytics

The Data Analytics Team headed by Prof. Dr. Ir. Wouter Verbeke is a small team of big data scientists within the BUTO department at the Faculty of Economics and Social Sciences. The team is closely linked to both MOBI and SMIT research groups and cooperates on a regular basis with several academic and industrial partners.

The team develops, applies and evaluates analytics for business applications such as credit risk modeling, customer relationship management and profitability modeling, demand forecasting and supply chain analysis, fraud detection and human resources management. The objective is to develop and adapt analytical tools to take into account the operational business setting where these tools will be implemented and applied for improved decision making. This is a unique perspective within the field of Big Data which drastically differs from a statistical or IT perspective, since management typically has specific concerns when adopting analytical solutions, such as the interpretability and user friendliness of representations and implementations of analytical models, the impact on revenues, costs, and profits when automating decision making based on a data-driven modeling approach, etc.

The research team has a solid business expertise and a broad experience in setting up projects in cooperation with the industry, ranging from small-scale experimental evaluations of analytical approaches for specific business goals to the development and implementation of novel data driven solutions and techniques to address and explore emerging business opportunities. The goal of these collaborations for the business analytics team is to gain insight and deeper understanding as well as to develop expertise leading to scientific publications, while at the same time delivering as much valuable and useful research insights, knowledge and output to the business project partner.

 

Members

 

Permanent staff

 

Last name First name

Phone: +32 2 629 xx xx
Email: 
Office: 

Research domain: 
Publications

 

 

 

 

 

 

Associated staff

Last name First name

Phone: +32 2 629 xx xx
Email: 
Office: 

Research domain: 
Publications

 

 

 

 

 

 

 

 
 

 

Temporary research staff

 

 

Last name First name

Phone: +32 2 629 xx xx
Email: 
Office: 

Research domain: 
Publications