Hi @Landan George​ ,

Thank you for sharing this notebook and also your insight. Sorry about not being clear with my statement above. What I meant was, if I have a preprocessing pipeline which does some transformation (such as one-hot-encoding or scaling the numerical values) on data before training, then we have to store the fitted functions for preprocessing as pickles and then once a new set of raw inference data in batch arrives, we have to apply transform functions on the raw data, so that it gets the format of training data. But what I thought genuinely the FS save the mapping of the transforamtion inside it and once we get new raw data for inference we do not need to load those pickled functions and apply it to them and we can directly transform them using FS capabilities. But I am assuming this functionality is not part of feature store yet. right?