Bayesian networks are particularly useful in the fields of artificial intelligence, big data and smart data as well as industry and Factory 4.0. They are a helpful tool for dealing with large amounts of data and making decisions when not all the information is available.
A Bayesian network is a model that shows how different factors or events are interrelated and can influence each other. The special thing about it is that you can make good predictions even with incomplete data.
Imagine predicting machine failures in a factory. A Bayesian network takes into account various influencing factors such as temperature, maintenance intervals or machine types. For example, if you only know that the temperature was high and maintenance is due, the network can still calculate how likely a breakdown is - and do so very precisely.
Bayesian networks help companies to better assess risks, optimise production processes and intelligently evaluate large volumes of data. They help wherever fast and reliable decisions are required, even if not all the facts are on the table.
Deutsch 
English (UK)