749 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.
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Latest tutorials
Page 34 of 125- 01Lakehouse 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
- 02Event-Driven Table Compaction with AgentsEvent-driven compaction is valuable when agents coordinate maintenance with workload signals, table health, and commit safety.LakehouseJun 22, 2026
- 03Fabric Agentic Analytics and Lakehouse Schema DesignMicrosoft Fabric agentic analytics is a reminder that schemas, semantic models, and governed lakehouse design now shape AI behavior.LakehouseJun 22, 2026
- 04Fine-Grained Security for AI AgentsMachine-speed analytics requires machine-enforced policy, identity, masking, filtering, and audit controls.LakehouseJun 22, 2026
- 05Iceberg v4 Performance: Root Manifests and CallsApache Iceberg v4 discussion should focus on planning cost, metadata layout, and object storage round trips, not vague claims about faster tables.LakehouseJun 22, 2026
- 06What Is LTAP in the Lakehouse?Lakehouse transactional analytical processing is useful only when teams define freshness, isolation, and workload boundaries clearly.LakehouseJun 22, 2026