For the person who owns the data platform, an analytics decision is really a data-path decision. The feature list matters less than three questions: where does the data go, what leaves your environment, and who can see what. Those are the questions a CTO is accountable for long after the demo.
Every tool wants a copy
The default pattern in analytics is to take a copy. Another vendor, another export of your player database sitting somewhere you do not control. Warehouse-native is worth asking about precisely because it changes this: the aim is to work against your governed data and metric layer rather than hold a separate copy. The honest version of the claim is specific, so ask for the actual data path you will deploy, including what is retained and for how long.
Self-service without giving up control
The tension a CTO manages is real. Business teams want to ask their own questions; you own the access model that keeps player data safe. The resolution is not to refuse self-service but to scope it: roles and permissions per product and category, a consent log, and login history that is reviewable. Teams get answers within their scope, and the scope is yours to set.
One definition, not one per tool
A quieter benefit of a governed metric layer is engineering hygiene. When every dashboard reimplements NGR, the numbers drift and you field the tickets. A shared definition that the whole workspace reads from means a measure means the same thing in chat, in a report and in a score, and business context that teams add is reviewed before it is used.
It runs where you run
The deployment stance is the summary of all of it: Bounty runs inside your environment, so no copy of your database has to leave it, and you keep control of access and freshness. That is the part a CTO can actually stand behind.
The right question is not what the AI can do, but where your data goes while it does it.