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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. 01Data Vault Modeling: Hubs, Links, and SatellitesDimensional modeling works well when your source systems are stable and your business questions are predictable. But what happens when sources change constan...
  2. 02Data Modeling Best Practices: 7 Mistakes to AvoidA bad data model doesn't announce itself. It hides behind slow dashboards, conflicting numbers, confused analysts, and AI agents that generate wrong SQL. By ...
  3. 03What Is a Semantic Layer? A Complete GuideAsk three teams in your company how they calculate revenue and you'll get three answers. Sales counts bookings. Finance counts recognized revenue. Marketing...
  4. 04How to Build a Semantic Layer: A Step-by-Step GuideMost teams start building a semantic layer the wrong way: they open their BI tool, create a few calculated fields, and call it done. Six months later, three ...
  5. 05Semantic Layer vs. Metrics Layer: What's the Difference?Both terms appear in every modern data architecture diagram. They're used interchangeably in conference talks, Slack threads, and vendor marketing. And almos...
  6. 06Semantic Layer vs. Data Catalog: Complementary, Not CompetingWe already have a data catalog, so we don't need a semantic layer. This is one of the most common misconceptions in modern data architecture.