696 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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  1. 01Why Your AI Initiatives Fail Without a Semantic LayerYour team builds an AI agent. It connects to your data warehouse. A product manager types What was revenue last quarter? and gets a number. The number is wrong.
  2. 02The Role of the Semantic Layer in Data GovernanceMost organizations have a data governance policy. It lives in a Confluence page. It defines who owns what data, what terms mean, and who should have access. ...
  3. 03Data Virtualization and the Semantic Layer: Query Without CopyingEvery data pipeline you build to move data from one system to another costs you three things: time to build it, money to run it, and freshness you lose while...
  4. 04Headless BI: How a Universal Semantic Layer Replaces Tool-Specific ModelsYour organization uses Tableau for executive dashboards, Power BI for operational reports, and Python notebooks for data science. Revenue is defined in Table...
  5. 05How a Self-Documenting Semantic Layer Reduces Data Team ToilEvery data team knows documentation is important. And almost every data team has a backlog of undocumented tables, unlabeled columns, and outdated descriptio...
  6. 06Semantic Layer Best Practices: 7 Mistakes to AvoidSemantic layers don't fail because the technology is wrong. They fail because of design decisions made in the first two weeks : choices that seem reasonabl...