"quare id inferam fortasse requiris"

Can a single probabilistic model deliver robust and tractable inference
in presence of uncertainty over inputs (e.g., missing values, noise,...)
and detect anomalous values while dealing with heterogeneous
(mixed continuous and discrete, different likelihood models and statistical data types)?
Can we use it for exploratory data analysis?
Which kind of (probabilistic) patterns will it discover?