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Business Data Analytics

The research group “Business Data Analytics” dedicates its work to create value for society and businesses from the opportunities created by Analytics/AI and Big Data. We do research and education on Business Case Identification, Method Hybridization, Data Fusion, and Incentive Engineering in diverse contexts.

Head of Area

Dr. Alexander Gröschel
+49 (721) 9654-804
groeschel∂fzi de
  Simon Kloker

Dr. Simon Kloker
+49 (721) 608-48383
simon.kloker∂kit.edu

 

 

Members

Wolfgang Badewitz
+49 (721) 9654 809
badewitz∂fzi.de
  Nicolas Haubner
+49 (721) 9654 818
haubner∂fzi.de
  Felix Kiefer Felix Kiefer
+49 (30) 7017337-345
kiefer∂fzi.de

Barbara Stöckel
+49 (721) 9654 826
stoeckel∂fzi.de

 

Marius Lämmlin
marius.laemmlin

∂student.kit.edu

Domains

  • Automotive
  • Health Care
  • Industry 4.0
  • Mobility
  • Public Management
  • Telecommunications

Methods

  • Statistical Learning
  • Combinatorial Optimization
  • Data Dimensionality Reduction
  • Feature Extraction and Generation
  • Incentive Engineering
  • Data Fusion
  • Method Hybridization

Projects:

  • Concise representation of cash flow forecasting- and revisioning-behavior processing analytical-orthogonal and Bayes-based metrics in corporate financial controlling (in collaboration with Bayer AG)
     
  • Non-addictive Information Systems

  • Design of robust and concise metrics to represent and cluster the purchasing and usage history of telecommunication customers used in campaign management (in collaboration with a global telecommunications company)
     
  • Techniques to decompose constraint matrices in packing problems and step-wise generation of variance-preserving, pseudo-perpendicular constraints aimed at transforming high-dimensional MIP into lower-dimensional problem representations that allow for more efficient and scalable problem solving (in cooperation with Siemens AG)

  • ReKoNet
     
  • Productive 4.0

 

Former Projects

  • Accuracy improvement of vast amounts of heterogeneous judgmental cash flow forecasts using analytical debiasing methods and combination with model forecasts (in collaboration with Bayer AG)
     
  • Concise representation of cash flow forecasting- and revisioning-behavior processing analytical-orthogonal and Bayes-based metrics in corporate financial controlling (in collaboration with Bayer AG)
     
  • Modelling and prediction of user behavior related electric vehicle high-voltage battery aging, based on heterogeneous field-data (in collaboration with a large German OEM)
  • Design of robust and concise metrics to represent and cluster the purchasing and usage history of telecommunication customers used in campaign management (in collaboration with a global telecommunications company)
     
  • Development of novel analytical approaches in the context of Geographic Information Systems (GIS) that allow a faster and more reliable consideration of vast amounts of heterogeneous and unreliable data in disaster and emergency management (BMBF-founded Project; program: Big Data
     
  • Techniques to decompose constraint matrices in packing problems and step-wise generation of variance-preserving, pseudo-perpendicular constraints aimed at transforming high-dimensional MIP into lower-dimensional problem representations that allow for more efficient and scalable problem solving (in cooperation with Siemens AG)