On completion of the course, the student should be able to:
compile and analyse complex customer and market data, such as "Big Data", using databases and computer-based tools,
model and simulate innovation processes as well as analyse and evaluate market data as input to product development operations,
account for and apply methods and techniques that can be used to study and analyse user situations.
Cross-disciplinary analysis models and analysis tools for the analysis of very large databases, where data is characterized by high variations in data quality, data types and data sources as well as timeframes. Innovation adoption models and technology adoption forecasts, strategic business planning and product portfolio and product line planning.
Lectures, laboratory exercises, seminars and project work in group.
Written and oral presentation of project group work as well as active participation in seminars, laboratory exercises (2 credits). Writen exam (3 credits).
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.