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.
Browse by topic
All topics- Data Lakehouse201
- Data Engineering178
- Apache Iceberg147
- Dremio65
- AI Agents52
- developer tools33
- AI coding tools31
- agentic development31
- Databases28
- MCP28
- Data Architecture24
- AI23
- Apache Polaris23
- Semantic Layer23
Latest tutorials
Page 56 of 116- 01Star 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...Data ModelingFeb 19, 2026
- 02Data 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....Data ModelingFeb 19, 2026
- 03Dimensional Modeling: Facts, Dimensions, and GrainsDimensional modeling is the most widely used approach for organizing analytics data. Developed by Ralph Kimball, it structures data into two types of tables:...Data ModelingFeb 19, 2026
- 04Slowly Changing Dimensions: Types 1-3 with ExamplesDimensions change. A customer moves cities. A product gets reclassified. An employee changes departments. How your data model handles these changes determine...Data ModelingFeb 19, 2026
- 05Data Modeling for Analytics: Optimize for Queries, Not TransactionsThe data model that runs your production application is almost never the right model for analytics. Transactional systems are designed for fast writes : in...Data ModelingFeb 19, 2026
- 06Denormalization: When and Why to Flatten Your DataNormalization is the first rule taught in database design. Eliminate redundancy. Store each fact once. Use foreign keys. It's the right rule for transactiona...Data ModelingFeb 19, 2026