normalising data before data split or after?

Hi,

I have a question, I wanted to separate my data into train and test set, should I now apply normalisation before or after the split?

someone told me it would make more sense to do normalisation after the split for each train /test data... but why? if I do so, I would normalise on the specific ranges of values regarding the train / test dataset...

but if I use split before, I will normalise on the whole range, isn't that more general, and therefore more representative regarding my dataset? or does it make no difference at all?
Please help.

Thanks!

I didn't find the right solution from the Internet

References:
communitysfdgfdxg.rapidminer.com/t5/RapidMiner-Studio-Forum/normalising-data-before-data-split-or-after/td-p/32592
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