Data Science

Data Science



What is Data Science?

“Data Science” is a summary term for efforts related to use data to generate insights for business. It is a response to the vast amounts of data available to firms due to the digitalization of society. Data Science covers all aspects of data analysis. It can be based on small and large samples, using from few to very many variables, and have descriptive, exploratory, and explanatory goals. Data sources do not need to be numbers, but may well include texts, images, and social links.


How is Data Science different from Statistics?

Data Science (as we understand it) always starts with some sort of business problem. Also, it does not stop at computing results, but seeks to make them “actionable.” Data scientists always think hard about how their methods and analyses can improve decision-making and (ultimately) create business value. That said, statistics are of course at the core of data science.


What makes Data Science attractive?

Harvard Business Review has identified becoming a “Data Scientist” as the most attractive job of the 21st century. While some professors, footballers, or gardeners may see their job in the top position, Data Science surely is a very attractive subject. “Data Scientists” need to have a broad spectrum of interdisciplinary skills, ranging from data management, business intelligence systems implementation, marketing, data visualization, statistical methods, machine learning algorithms up to presenting, communicating and making extracted insights actionable. Working as a data scientist, will require you to develop your potential to the fullest. That has a lot of appeal (we think).

Moreover, the increase in data available to firms has not been matched by a similar increase in individuals with the right mix of quantitative skills and business intelligence. In other words, firms are actively searching for data scientists and they pay good money to hire them.


What are we offering?

We are constantly receiving inquiries from firms wanting to hire data scientists. That’s why we decided to offer a specialization “Data Science” as part of the KIT curriculum for students studying Industrial Engineering & Management (Wirtschaftsingenieurwesen) or Information Engineering & Management (Informationswirtschaft). Four core “Data Science” modules are offered by professors of the Institute of Information Systems and Marketing (IISM). They are all eligible as “BWL” courses in our master programs. With a common header “Data Science” in the module titles, your focus on data science will also be clearly visible on your diploma.


Data Science: Advanced CRM
  • Social Network Analysis in CRM (Geyer-Schulz)
  • Recommendsysteme (Sonnenbichler)
  • Intelligente CRM Architekturen (Geyer-Schulz)
  • ...
Data Science: Data-Driven Information Systems
  • Service Analytics (Setzer/Fromm)
  • Buisness Intelligence System (Mädche)
  • Buisness Data Strategy (Weinhardt)
  • Data-Driven Information Systems(Weinhardt/Mädche/Setzer)
Data Science: Data-Driven User-Modeling
  • Experimentelle Wirtschaftsforschung (Dorner/Pfeiffer/Teubner)
  • Crowd Analytics (Weinhardt/Teubner)
  • Modeling & Analyzing Consumer behavior with R (Dorner)
Data Science: Evidence-based Marketing
  • Marktforschung (Klarmann)
  • Marketing Analytics (Klarmann)


Additionally, on this website we identify further courses from other domains that could complement these four modules. Domains include Operations Research, Computer Science, and Econometrics/Statistics

Certificate Course_DataScientist
Certificate Course "Data Science@HECTOR School"

The certificate course Data Science@HECTOR School conveys knowhow on methods as well as statistic techniques and models to indicate, analyze and forecast relevant developments (e.g., consumer behavior) for different business segments.

Call for Teams: Data Science Game 2017

Data Science Game is a French organization run by volunteers. The aim is to build briges between members of the data science community all around the world. Each year, an international data science competition for students interested in computer science, engineering, statistics and applied mathematics is organized... more

New Publication in Decision Support Systems (DSS)

The DSS published a research paper by Dr. Stefan Morana, Dr. Silvia Schacht, Ansgar Scherp, and Prof. Alexander Mädche. In their paper they theorized an integrated taxonomy on guidance design features by categorizing exisiting research on decision support and decision-making. more...

Business Intelligence Systems Capstone Projects finalized

On February 9th, 2017, seven teams of the lecture “Business Intelligence Systems” (BIS) presented the results of their capstone project in the KD2Lab at KIT. The capstone project was done in cooperation with KPMG AG  as part of the Business Intelligence & Analytics Lab... more

Research Assistant "Self-Service Analytics" in cooperation with Bosch Group

This job position is funded by the project “Self-Service Analytics” in cooperation with the Bosch Group. The project is set up for three years and aims at developing new concepts in the area of Business Intelligence & Analytics (BI&A)... more