FreeEbook

The Architecture Your AI Analytics Agent Actually Needs

A practical guide to query federation, the AI Semantic Layer, Apache Iceberg, and lakehouse architecture for teams building agentic AI on real enterprise data.

The Architecture Your AI Analytics Agent Actually Needs cover

What's Inside

  • Why ETL pipelines actively break your AI agents
  • How zero-copy query federation spans every data source
  • The AI Semantic Layer that gives agents business context
  • A 5-phase roadmap from data connection to agent activation

Written by Alex Merced, Developer Advocate at Dremio. Validated by Fortune 500 data architects.

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EBOOK OVERVIEW

What You'll Learn

A complete technical guide to the data architecture that makes AI analytics agents fast, trusted, and production-ready.

Zero-ETL data access

Learn how query federation reaches every source without moving data, and how the AI Semantic Layer gives agents the business definitions they need to return accurate insights.

Agent-ready data foundation

Understand how Apache Iceberg and Apache Polaris create an open, governed catalog that any agent, LLM, or analytics engine can query with consistent performance and access controls.

Roadmap to agentic activation

Follow a 5-phase deployment framework covering connection, documentation, acceleration, governance, and activation, with real industry scenarios across retail, financial services, manufacturing, and healthcare.

Alex Merced
Featured Author

Alex Merced

Developer Advocate, Dremio

Alex Merced is a Developer Advocate at Dremio and a leading voice in the Apache Iceberg and data lakehouse community. He writes and speaks extensively on query federation, the AI Semantic Layer, and agentic data architectures, helping engineering teams build production-ready AI analytics systems on open standards.

Put your AI agents on a real data foundation

Apply the federation, semantic layer, and Iceberg architecture your agents need to deliver trusted insights at production scale.

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