Getting up to speed fast on modern data stacks (for non-technical person)?

Hey folks - I'm trying to get up to speed ASAP to understand the modern data stack. I come from a non-technical background, so much of what I've been reading is a bit hard to understand...My goal is to try to understand the modern data stack (esp at tech companies) from a first principles approach. -> What are the best resources (besides this website 😃) for someone like myself to gain a comprehensive understanding of the modern data stack?Here are some of the more important questions I would like to be able to answer (eventually).- What does the progression of stack/tools change over time as a company goes from a startup to a larger enterprise? In particular, what does this look like at the critical point when you have disparate tools (e.g. CRM, Google Analytics, Product Telemetry, etc.) and you want to consolidate them into one place?- How teams choose how to architect their stack (pros and cons and tradeoffs of different approaches)- How are the problems that data teams face at smaller companies different than those at bigger companies? - How do teams address the problems around messy, undefined, redundant data effectively? I know there are tools out there that can help, but I have a feeling that it's not necessarily a software problem.