I've observed that many of the datasets available for traditional ML and data science algorithms seem to be in the order of MB. I assumed these may be because earlier computers were not that computationally efficient. However, someone pointed out it need not be the case. Many of the training datasets are smaller in size.
I want to ask whether or not using a huge dataset for training/inference on traditional ML and data science algorithms makes sense? Is it a proper use case? If yes, can someone please point me towards such a huge dataset available online?