795 tutorials · free to read
A working handbook for data and software engineering.
Hands-on tutorials by Alex Merced on Apache Iceberg, the data lakehouse, pipelines, agentic AI, and the languages and tools that hold it all together.
Follow an ordered learning track with prerequisites and checkpoints →
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Latest tutorials
Page 38 of 133- 01Autonomous Materialization for Agentic AnalyticsAutonomous materialization is useful when it is tied to workload evidence, governance checks, and lifecycle management.LakehouseJun 22, 2026
- 02Composable Semantic Layers for Analytical AgentsAI agents need more than metric names. They need composable business logic that survives multi-step analysis.LakehouseJun 22, 2026
- 03Built for Agents and Managed by AgentsDremio Agentic Lakehouse is easiest to understand as two ideas: data built for agent access and platform work managed by agents.LakehouseJun 22, 2026
- 04ClickHouse in the Loop for Active AgentsLow-latency analytical systems can help active agents, but only when event loops include validation, context, and safety boundaries.LakehouseJun 22, 2026
- 05The Context Layer for AI AgentsA semantic layer is necessary, but agents also need lineage, quality, freshness, compliance, and ownership context.LakehouseJun 22, 2026
- 06Lakehouse as the Operating Layer for Agentic AIAgentic AI announcements are useful when they validate the need for governed data, semantic context, and cost-aware execution.LakehouseJun 22, 2026