This article outlines Zeta's approach to building a composable, scalable lakehouse architecture that integrates diverse data sources. It details how they manage data efficiently across multiple accounts while maintaining governance and flexibility for AI-driven workloads.

Organizations face significant challenges in scaling AI proofs of concept (POCs) into production, with nearly 40% remaining stuck at the pilot stage. The FOREST framework outlines six dimensions of AI readiness—foundational architecture, operating model, data readiness, human-AI experiences, strategic alignment, and trustworthy AI—to help organizations overcome barriers and successfully implement AI initiatives.