Databricks tutorial dimensional modeling for the gold layer
The video explains why dimensional modeling is a crucial step before building the Databricks gold layer, emphasizing alignment between business stakeholders and developers so the warehouse actually supports the business. Using Kimball-style star schema concepts, it distinguishes fact tables (quantitative event data at a chosen grain) from dimension tables (context for analysis) and shows how they join to serve downstream users via specialized/materialized views. It references prior work in the silver layer, where cleaned supply chain data was consolidated into an OBT, and uses those columns to design a simplified star schema in dbdiagram. It builds a fact_order_lines table and dimensions for product, customer, order, and date, explains current vs order-time product price, and demonstrates linking tables with crowfoot notation and foreign keys. The result is an implementation-ready physical diagram to be created in Databricks next.
Github repo
https://github.com/kokchun/databricks...
Video on dimensional modeling concepts
• Dimensional modeling with star schema (the...
#starschema #kimball
00:00 Why Dimensional Modeling
01:13 Star Schema Basics
02:29 Silver Layer Source Data
03:41 Setting Up DB Diagram
05:24 Building the Fact Table
07:12 Creating Dimension Tables
09:08 Linking Tables with Refs
12:31 Final Schema and Next Steps
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