This ebook provides a comprehensive overview of the lakehouse architecture and its role in enabling advanced analytics and AI at scale. It explains how lakehouses combine the structured reliability of data warehouses with the flexibility of data lakes to support diverse workloads, including BI, data science, and machine learning. The guide outlines key challenges organizations face with legacy architectures, such as data silos, performance bottlenecks, and rising costs, and shows how lakehouses address these issues. It emphasizes governance, scalability, and real-time analytics as foundational requirements for AI readiness. Use cases demonstrate how lakehouse platforms accelerate insights, improve collaboration, and support enterprise-wide AI initiatives.

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