The patterns that survive the platform underneath.
A vendor-neutral practitioner's reference for analytical data warehousing. Pillar articles on the seven topics we cover in depth, technique deep-dives on the specific moves that determine whether a warehouse holds up in production, and a working glossary that defines the vocabulary as it's actually used.
Dimensional Modeling.
Star schemas, fact and dimension tables, grain, surrogate keys, slowly changing dimensions, and the design choices that determine whether a model holds up in production.
20 entries across the pillar article, technique deep-dives, comparisons, and the glossary develop this subject.
Enter the topic →The seven subjects this publication covers.
Each topic groups the pillar article, the technique deep-dives, the comparisons, and the glossary entries that develop the subject.
Warehouse Fundamentals
What a data warehouse is, the architectural patterns, the relationship to lakes and lakehouses, and where the warehouse sits in the modern data stack.
22 entries
Dimensional Modeling
Star schemas, fact and dimension tables, grain, surrogate keys, slowly changing dimensions, and the design choices that determine whether a model holds up in production.
20 entries
Data Vault Modeling
Hubs, links, satellites, the data vault philosophy, and when the vault is the right model for an integration-heavy warehouse.
1 entry
Loading and Operations
ETL versus ELT, change data capture, incremental loading, watermarking, idempotency, and the operational disciplines that keep production warehouses correct.
24 entries
Modern Warehouse Platforms
Snowflake, BigQuery, Redshift, Databricks, and the platform-level trade-offs that shape how a warehouse is built on top of them.
7 entries
Warehouse Automation
Model-driven generation, metadata-driven pipelines, the design-time-versus-runtime question, and where automation actually moves the needle.
6 entries
Analytics Modeling
Modeling for OLAP, semantic layers, metric definitions, and the relationship between warehouse modeling and the BI tools that sit on top.
1 entry
Technique
Advanced dimensional modeling: bridge tables, inferred members, multi-timezone, and the awkward cases
2026-05-15
Technique
Building a data warehouse: a four-phase practitioner's playbook
2026-05-15
Technique
Data cleansing in the warehouse: where it belongs and what it does
2026-05-15
Technique
Data extraction models: full, incremental, log-based, query-based, file-based, API, and streaming
2026-05-15
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