: Dimensions stored directly in the fact table (like an invoice number) without a separate table.
: Methods to track history when attributes change (e.g., when a customer moves to a new city). Type 1 : Overwrite the old data. Type 2 : Create a new row to preserve history (most common). Type 3 : Add a "previous value" column.
: Uses "Conformed Dimensions" (standardized lists like a master customer list) so different data marts can "talk" to each other. Kimball & Ross - The Data Warehouse Toolkit 2nd...
Unlike traditional normalized databases (ER Modeling), dimensional modeling organizes data into two specific types of tables:
: Used to handle "many-to-many" relationships, such as an account with multiple owners. ⚖️ Kimball vs. Inmon The book is often contrasted with Bill Inmon’s approach: Kimball (Toolkit) Inmon (Corporate Information Factory) Philosophy Bottom-up / Decentralized Top-down / Centralized Structure Dimensional (Star Schemas) Normalized (3rd Normal Form) Speed Faster to implement for specific departments Slower; requires enterprise-wide planning Primary Goal Ease of use and reporting Data integrity and "single version of truth" 🚀 Why It Still Matters : Dimensions stored directly in the fact table
Explain the for project management. Provide SQL examples of how to implement a Type 2 SCD.
for a specific industry (Retail, Finance, Healthcare, etc.). Type 2 : Create a new row to preserve history (most common)
: The primary goal is high performance and ease of use for the end business user.