The importance of data exploration and hypothesis building - Past session

Having a clear idea of the business opportunity and having a library of intelligent algorithms at your disposal is not sufficient for realizing a data-driven solution. Having a detailed understanding of the available data in order to derive viable working hypotheses about the underlying mechanisms of the problem under study is just as important. Is the data suitable to solve the business challenge? Is it of the right quality and nature? What data is missing?  Does it exhibit significant patterns and trends that can be exploited to model and understand better the problem under study? In this session several data exploration approaches will be discussed, with particular attention for numerical and visual data exploration techniques.

Target audience 

The mastercourse is open to any company that is interested in data innovation as an opportunity for its company and activities. For this session some basic analytic skills (e.g. high level understanding of algebra and interpretation of statistical figures) are a prerequisite.

Further registration & information:

Contact: Caroline Mair ( )


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