The section Business Analytics includes about 50 people; faculty members, teaching staff, PhD students and affiliated faculty. The Business Analytics section fosters a lively academic climate. We frequently organise academic seminars and reading groups and regularly invite external visitors.
Members of the section Business Analytics do research and teach in a broad range of areas of business analytics and operations management. The section Business Analytics has four main areas of expertise. Read more about our main research area's.
In our research we focus on analysis of large and heterogeneous data collections and facilitating access to them. What makes our approach unique is using domain knowledge and theories from relevant business disciplines for creating new generation of human-centered multimedia, computer vision, information retrieval and machine learning techniques. We are also teaching a variety of courses related to artificial intelligence for business, ranging from algorithms and data structures, machine learning and deep learning to language technology and text retrieval and mining.
Digital Business is concerned with using IT to create business value. This includes IT-strategy, data-driven innovations, technology adoption, IT governance, IT development and deployment as well as digital transformation. We approach these areas from an organisational or socio-technical perspective, using either qualitative, quantitative or design research methods.
Data plays a vital role in our society. In the field of statistics, we use these data to analyse and improve problems in businesses and society. Our researchers in this area are focused on data-driven methods of operational excellence, as well as statistical techniques for modeling and monitoring process performance. Part of the research revolves around methodological process improvement frameworks such as Lean Six Sigma, and the challenges around implementation and adaptation of these methodologies. Another research focus is on the technical tools in statistical modeling that can be used to identify important influence factors, and methods to aid in statistical and predictive process monitoring. The application areas are broad, with examples in industry, healthcare, and financial services, amongst others.
In Operations Research we develop new mathematical models and techniques to improve data-driven decision making. Key element is often how to deal with uncertainty. Mathematical Optimization is important to find the best solution. Optimization for and with Machine Learning is another important research topic for us. We also apply Operations Research in practice to improve decision making in business and society.
The members of the section Business Analytics teach in Bachelor's, Master's and Executive Programmes. Read more about our education.
Our staff is associated with various research initiatives and platforms, e.g. the Analytics Academy, the brand new Analytics for a Better World iniviative, the Institute of Business and Industrial Statistics (IBIS UvA). IBIS is seen internationally as a centre of expertise in Lean Six Sigma, operational excellence and industrial statistics. The section is currently developing a Business Analytics Centre. All institutes are affiliated with the University of Amsterdam.