I've been reading about machine learning models deployment and pipelines and so far most of the sources suggest that the data should be ingested from some sort of cloud based storage or source, be it AWS S3, Kaggle, Bigquery or whatever else.
Now the thing is that in my company we analyze sensitive client data which i think should not be stored in the cloud as its a potential security threat, or at least it should not leave the country/EU because of GDPR.
So given this how machine learning pipelies can use offline, local data to work?