Most data teams jump straight from a stakeholder request to creating database tables. They skip the planning steps that prevent misalignment, redundancy, and...

Both star schemas and snowflake schemas are dimensional models. They both organize data into fact tables (measurable events) and dimension tables (context ab...

Traditional data modeling assumed you controlled the database. You defined schemas up front, enforced foreign keys at write time, and optimized with indexes....

Dimensional modeling is the most widely used approach for organizing analytics data. Developed by Ralph Kimball, it structures data into two types of tables:...

Dimensions change. A customer moves cities. A product gets reclassified. An employee changes departments. How your data model handles these changes determine...

The data model that runs your production application is almost never the right model for analytics. Transactional systems are designed for fast writes — in...