[anonu]

Some thoughts:

- a clean data pipeline is critical. Is your data pipeline manageable? Is it observable? Is it monitorable? Can you make changes quickly at different stages? How do overrides work? Does your data pipeline have entitlements? (Can private data points be provisioned to specific users?)

- Should you implement your own dashboard? Or are you reinventing the wheel? Can you reuse/recycle existing BI tools? What are the licenses involved? Power BI is proprietary to microsoft and will have per user economics. Grafana is AGPL, be very careful with anything AGPL in your tech stack because it may force you to open source your code. Apache Superset is pretty cool. I've seen big startup valuations with off-the-shelf BI tools. If its an MVP, definitely consider using this as opposed to rolling your own.

- Making assumptions for your users is bad because users will always ask for more. So building a flexible framework where users can add/remove visuals and build their own analytics may be necessary. The flipside is this adds complexity and can confuse the user. Its a delicate balance to cater to all types of users: the basic user vs the power user.

- How do users send you feedback? Bad data point? How do you find out? Can the user address it themselves?