There’s no perfect model for product analytics—only evolving ones. This guide presents best practices for data modeling, from building raw and clean models in parallel to designing star schemas and managing append-only, denormalized data. It emphasizes principles like data governance, time-series precision, and pre-compute vs. on-the-fly metrics. Featuring 10 use cases and a streaming provider case study, it illustrates how Kubit enables fast, scalable analytics using warehouse-native architecture.

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