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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All topics- Apache Iceberg202
- Data Lakehouse200
- Data Engineering182
- Dremio65
- AI Agents61
- developer tools35
- Apache Polaris33
- AI coding tools31
- Semantic Layer31
- agentic development31
- MCP29
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Latest tutorials
Page 52 of 133- 01When Paimon Beats Iceberg for Mutable StreamsApache Paimon uses LSM-Tree storage for native CDC upserts without restart. Learn when Paimon outperforms Iceberg for high-churn mutable streaming workloads.Apache IcebergMay 24, 2026
- 02Policy as Code for Lakehouse GovernanceOPA, ABAC, row filters, and column masks make lakehouse governance programmable and scalable. Learn how Databricks, Snowflake Horizon, and BigQuery implement policy-as-code.Data LakehouseMay 24, 2026
- 03Real-Time Lakehouse Patterns with Apache Flink and IcebergLearn how to build a real-time lakehouse with Apache Flink 2.1 and the Dynamic Iceberg Sink, covering schema evolution, exactly-once delivery, and compaction.Apache IcebergMay 24, 2026
- 04Why Semantic Layers Make Enterprise Text-to-SQL SaferText-to-SQL accuracy jumps from 40% to 85-95% when grounded in a semantic layer. Learn how Dremio, Snowflake Cortex Analyst, and dbt Semantic Layer improve AI analytics reliability.Data LakehouseMay 24, 2026
- 05Single-Node Data Engineering: DuckDB, DataFusion, Polars, and LakeSailOptimize single-node data engineering with DuckDB, DataFusion, Polars, and LakeSail. Compare architectures and learn when to transition to Dremio MPP.Data LakehouseMay 24, 2026
- 06Choosing Vector Stores for Retrieval Workloadspgvector, Milvus, Weaviate, and LanceDB each make different tradeoffs on index type, hybrid search, scale, and operational complexity. Learn which fits your retrieval workload.Data EngineeringMay 24, 2026