4 docs tagged with "DWH"

Dimensional modeling is the standard technique for structuring data warehouses for analytical queries. It organizes data into fact tables and dimension tables to optimize read performance and business usability.

Fact tables are the core of any dimensional model. Their design directly impacts query performance, storage efficiency, and analytical flexibility.

This document defines enterprise-grade, scalable, and cost-efficient standards for a PySpark + S3 Iceberg + Snowflake External Volume + dbt architecture.

Slowly Changing Dimensions (SCD) handle the problem of dimension attributes that change over time. The chosen SCD type determines how historical values are preserved or overwritten.