If data products are critical data sets, their impact is measured by the breadth of use-cases they support.
I'm a data team of one in a Series A startup, and I'm new to the modern data stack. Our current data stack is RedShjft warehouse, DBT (manged by one of our software engineers until I get up to speed), FiveTran, and Looker for semantic layer/visualization. I feel like the Warehouse/ELT/Data Viz combo is the true MVP for a team of one, unless you're just truly a competent data engineer and analyst already, which I think is typically rare for teams of one. A summary of the "How does this evolve over time as your team does?" responses would be super helpful for me as I start to figure out next steps for either a) growing the team and what direction to go or b) what next tools we need to bring in (data visibility, data quality, etc.).