Agreed on most of what you said. DS doesn't necessarily need a lot of data. Alot of DS work is not much more than visualizations and report generation to find i

Agreed on most of what you said. DS doesn't necessarily need a lot of data. Alot of DS work is not much more than visualizations and report generation to find insights. ML might need a lot of data depending on how your org defines it. There are many interesting non-deep learning applications out there. At my org I was mostly involved in NLP work. Honestly I think that will be the big game changer for most of the Enterprise, as they primarily deal with text data. Think automated parsing and analysis of emails, chats, reports etc. Something like GPT-3, can be a game changer if/when it doesn't need a multi billion dollar super computer.