i'm curious about the tiny bits of context that prevent a big misunderstanding. something like 'partial week', 'refunds included', or 'this is per account, not per user'.

if you only had room for one extra sentence beside a chart, what would you put there? especially interested in a specific note that actually stopped repeat questions or changed how people read the numbers. a 30-page data dictionary probably isn't winning the attention contest lol.

Here's my mental model of the change happening in analytics.

• Ad hoc analytics are moving from spreadsheets to AI tools like Claude Dashboards.
• Good data and semantics were always important, still more so now. Semantics have a natual center of gravity close to the data
• Business Intelligence tools were losing the battle for the semantic layer . Now they're also losing the battle for analytics creation. So they are basically left with a deployment layer, but a slow, expensive one.
  
• Organizations still need to share analytics sometimes and have them refreshed, trusted and managed. Ideally they will also be fast and interactive and have some form of conversational analytics. Claude Dashboards doesn't do that.

First of all, is this how you're seeing the change happen?

Second: for those of you planning on using Claude dashboards or other AI builders, how are you planning to deploy analytics when needed? Like for in-product analytics for customers, or across your whole org? Are you using a BI tool that you already have, and how is that going?

My take is there's no way that legacy BI becomes the deployment layer for AI-based analytics. Would love to hear what you're doing or even just discussing at your shops.