The Era of Zero-ETL Federation: Fueling AI Agents with Real-Time Cross-Enterprise Data

This article discusses the shift from traditional batch ETL pipelines to zero-ETL federation for powering AI agents with real-time data. It explains how batch ETL introduces latency that limits agentic analytics, such as stale anomaly detection and decision lag. The federation architecture allows query engines to directly access data from source systems at query time, using predicate pushdown for performance. Practical patterns like real-time CRM and lakehouse joins are covered, along with tradeoffs and when federation works best. The article positions zero-ETL federation as the key data access layer for AI agents needing current, cross-enterprise data.