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 38 of 125- 01Apache Iceberg v3 Deletion Vectors on SnowflakeApache Iceberg v3 deletion vectors replace positional delete files with binary bitmaps in Puffin files, delivering up to 10x faster DML on Snowflake. Deep dive into architecture, benchmarks, and migration.Apache IcebergJun 08, 2026
- 02CDC Without Complexity Using Iceberg v3 Row LineageIceberg v3 row lineage adds _row_id and _last_updated_sequence_number to every table, enabling native change data capture without Debezium or Kafka. Technical deep dive with Snowflake and Databricks examples.Apache IcebergJun 08, 2026
- 03The 2026 Guide to Iceberg View FederationIceberg views standardize SQL view definitions across engines, enabling view federation across Polaris, Nessie, and Gravitino catalogs. How Snowflake Horizon, Databricks Unity Catalog, and open source catalogs handle portable SQL.Apache IcebergJun 08, 2026
- 04Microsoft Fabric Build 2026 Agentic Analytics StackMicrosoft Build 2026 revealed an agentic analytics stack built on Fabric IQ, OneLake Iceberg support, and semantic models. The architecture shows how Microsoft competes with open lakehouse platforms.Data PlatformsJun 08, 2026
- 05Implementing MCP in the LakehouseHow to build a Model Context Protocol (MCP) server that exposes lakehouse tables and semantic views as AI-accessible tools, with Python implementation patterns and authentication.AI & AgentsJun 08, 2026
- 06Modern Python Tooling for Apache IcebergPyIceberg, IceFrame, and the Iceberg CLI form a complete Python toolchain for Iceberg table management. Each tool targets a different workflow from metadata inspection to data engineering.Open SourceJun 08, 2026