About
About this data products library
A practical, structured reference for leaders and builders working across product, data, architecture, governance, and AI.
Purpose
The library is organized around decisions practitioners make: what to build, which architecture to choose, how to evaluate it, and how to operate it responsibly.
What you will find
Frameworks, visual guides, interactive comparisons, role playbooks, implementation tutorials, and reusable templates.
Editorial approach
Pages aim to make trade-offs explicit, connect technology to consumer outcomes, and distinguish production systems from demonstrations.
Author
Prashant Dhingra writes about data products, enterprise AI, generative AI, AI agents, and the architecture and operating models required to put them into production.
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