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On a technical level - this presents a problem. It’s not easy to evolve the underlying data models. Especially as users are trying to do more “self-serve analytics” with their reporting tools, they’ll ask for one-off dimensions to be added to a dashboard (e.g., “A flag for customers who have purchased the same product twice within 48 hours” or “Last-touch attributed channel, but excluding email”). The data models quickly become a tangled mess of limited-purpose logic to incorporate new dimensions, filters, metrics, and data sources. (View Highlight)

I’m skeptical that an LLM on top of the wild-west of a messy data warehouse can deliver the reliable results users need. Alternatively, an LLM querying a well-governed data model will face the same challenges as traditional BI tools. We will still need a flexible way to interact with and evolve our data models over time. (View Highlight)