What is a star schema in data warehousing?

A star schema is a modeling technique that organizes data into central fact tables for metrics and surrounding dimension tables for descriptive attributes, simplifying queries and improving performance.

Does it support complex relationship modeling?

Yes, it includes bridge table patterns to handle many-to-many relationships between dimensions and facts while maintaining the integrity of the star schema.

Can it help improve query performance?

Absolutely. The skill includes patterns for materialized views and aggregate tables that pre-calculate common metrics, significantly reducing the load on large fact tables.

How does this skill handle data history?

It provides standardized SQL patterns for Slowly Changing Dimensions (SCD), specifically Type 1 (overwrite), Type 2 (history via new rows), and Type 3 (history via new columns).

Data Warehouse Architect

Name: Data Warehouse Architect
Author: pluginagentmarketplace

bypluginagentmarketplace

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Database Management

Architects robust data warehouses using star schemas, dimensional modeling, and enterprise SQL patterns for scalable analytics.

About

This skill equips Claude with specialized expertise in architecting analytical databases using Kimball-style dimensional modeling. It provides implementation patterns for fact and dimension tables, sophisticated handling of Slowly Changing Dimensions (SCD), and performance optimization techniques through aggregate tables and bridge tables. By applying these patterns, users can build high-performance data environments that ensure historical data integrity and optimize complex analytical queries for business intelligence and reporting.

Key Features

1 GitHub stars
Bridge table patterns for many-to-many relationship management
Star schema and dimensional modeling implementation
Performance-focused materialized views and aggregate tables
Slowly Changing Dimension (SCD) Types 1, 2, and 3 logic
Conformed dimension design for cross-functional reporting

Use Cases

Designing an enterprise sales reporting system with centralized fact tables
Implementing history tracking for customer profiles using versioned SCD Type 2 rows
Optimizing dashboard performance with pre-calculated daily and monthly aggregate tables

About

Key Features

1 GitHub stars
Bridge table patterns for many-to-many relationship management
Star schema and dimensional modeling implementation
Performance-focused materialized views and aggregate tables
Slowly Changing Dimension (SCD) Types 1, 2, and 3 logic
Conformed dimension design for cross-functional reporting

Use Cases

Designing an enterprise sales reporting system with centralized fact tables
Implementing history tracking for customer profiles using versioned SCD Type 2 rows
Optimizing dashboard performance with pre-calculated daily and monthly aggregate tables