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A vertical-specific data app's potential can be measured against 5 criteria: does it have a strong point of view, durable process, manual validation, niche market, a prospective anchor client?

Data backend references architectures for 4 common data backend types: app-first, lake-first, warehouse-first, and the managed data backend.

Exploring two types of data experiences within applications: embedded analytics + vertical-specific data applications.

A note on the transition from CIFL to Cacheworthy, and the accompanying shift in focus from general-purpose data + analytics to user-facing data applications.

Learn the basics of the popular open-source data modeling framework: what's it used for, what it replaces, and how it helps you build more performant and maintainable analytics pipelines.