Question: Would you guys have any suggestions on golden ratios of • MLOps Engineers - Data Scientists • Data Engineers - Data Analysts ? We're trying to plan for growth in the company for the coming years

That sounds like a very company-specific question with no good default answer. Some things I would consider (in my very humble & subjective opinion): 1. Data Engineering need is mostly controlled by how much "data pipeing" is necessary. And that depends on the relative number & complexity of the domains you're sending data from. If you're above average, here, you will need more than average DEs, if not, you'll be fine with a lower number. 2. Data Analysts need is mostly controlled by how data-driven the decision making part of your company is, how good you are at turning data into valuable actions. Again, above average means more DAs. 3. ML Engineers & Data Scientists' need depends on how much your company strategy aligns with data. If data isn't yet a core part of the company strategy, then IMHO you'll need a below average number of them. If you are well aligned here, then you will need an above average number. And yes, I feel these guides will work for a couple of years to come as all of the underlying changes are hard & complex changes (you're not going to change & realign the company strategy over night, and neither the business domains you have). Hope that helps!

Awesome @Sven Balnojan thank you so much for the insights! We'll try to establish where our needs regarding data are, and grow in consequence 😄

Sure thing. Let us know what you finally decide 🙂