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> It's unlikely that a company needs to invest in data scientists or even thinking very hard about their data organization until the scale of their data is already pushing the bounds of what most RDMMSs can handle.

I work in an engineering data science consulting group for a major UK PLC. Almost all of our clients have mainly SQL based data sources, and none of them really require cloud scale. In fact I don't think I have come across a client whose data I can't handle in SQLite on my laptop.

However, the problems we solve do require data scientists - mainly STEM MScs with a smattering of PhDs who are capable of combining statistics, domain knowledge and the ability to work within a variety of organisations and present.






Seconding that. Several ‘AI’ startups I worked with, do not require a massive amount of data to create MVPs/first releases.

The do however invest early in sufficient data science functions to have a good liaison between the researchers and data acquisition.




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