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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. 01Pipeline Observability: Know When Things BreakAn analyst messages you on Slack - The revenue numbers look wrong. Is the pipeline broken? You check the orchestrator - all green. You check the target table...
  2. 02Data Engineering Best Practices: The Complete ChecklistBest practices documents are easy to write and hard to use. They list principles without context, advice without prioritization, and rules without explaining...
  3. 03What Is Data Modeling? A Complete GuideEvery database, data warehouse, and data lakehouse starts with the same question: how should this data be organized? Data modeling answers that question by c...
  4. 04Conceptual, Logical, and Physical Data Models ExplainedMost data teams jump straight from a stakeholder request to creating database tables. They skip the planning steps that prevent misalignment, redundancy, and...
  5. 05Star Schema vs. Snowflake Schema: When to Use EachBoth star schemas and snowflake schemas are dimensional models. They both organize data into fact tables (measurable events) and dimension tables (context ab...
  6. 06Data Modeling for the Lakehouse: What ChangesTraditional data modeling assumed you controlled the database. You defined schemas up front, enforced foreign keys at write time, and optimized with indexes....