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Explore how to integrate databases, data lakes, and real-time systems for AI workloads through three comprehensive conference talks from industry experts. Learn to build cost-efficient, high-performance AI architectures by integrating ClickHouse with Apache Iceberg, separating compute and storage while leveraging open table formats and caching strategies to accelerate queries on cold data. Discover how large language models can translate natural language questions into SQL on streaming data by combining Apache Kafka, Iceberg, and query engines via the Model Context Protocol, while addressing translation challenges, benchmarking, security, and adoption considerations. Master Amazon S3 Tables, AWS's fully managed Apache Iceberg service, including its core features such as atomic snapshots, high throughput operations, automated maintenance and compaction, performance tuning options, and migration paths for streaming analytics workloads. Gain practical insights through live demonstrations of query acceleration using swarm compute and caching, real-time pipeline construction with LLMs, and hands-on exploration of copy-on-write versus merge-on-read update modes, making this essential viewing for data engineers, architects, and AI practitioners working with modern data infrastructure.
