We can now collect, store, and process different kinds of data from formerly unconnected and unstructured sources through for instance sensor technology and Internet of Things. This enables us to answer massively complex, data-driven questions which it has previously not been possible to answer.

To enable students to answer such questions, the purpose of this course is to equip them with a toolbox of methods and application-related knowledge of how to explore relevant patterns, relationships, and trends in different kinds of data with the objective of making better informed decisions. The course aims at giving the students methods to collect and structure (datafication) and analyze both quantitative and qualitative data with relevance for business development and innovation. The course also introduces students to possibilities and techniques of utilizing big (large amounts of data), small (small samples) and deep (detailed) data and how to use such data to inform decisions on innovation, organizational and business development.
Target groupMaster
ECTS credits10 ECTS