Building Snowflake Schemas

1. Introduction

A snowflake schema is a type of database schema that is used in data warehousing and data modeling. It is characterized by its normalized structure, where dimension tables are split into additional tables. This design helps to reduce redundancy and improve data integrity.

2. Key Concepts

3. Building Process

Building a snowflake schema involves several steps:

1. Identify the Fact Table: Determine the key performance indicators you want to analyze.
2. Identify Dimension Tables: Identify the dimensions that will provide context to the facts.
3. Normalize Dimension Tables: Split any dimension tables into additional related tables to eliminate redundancy.
4. Define Relationships: Establish foreign key relationships between fact and dimension tables.
5. Implement the Schema: Create the schema in your database management system.

Example Schema Design

-- Create a fact table
CREATE TABLE sales_fact (
    sales_id INT PRIMARY KEY,
    product_id INT,
    customer_id INT,
    sales_amount DECIMAL(10, 2),
    sales_date DATE
);

-- Create a product dimension table
CREATE TABLE product_dim (
    product_id INT PRIMARY KEY,
    product_name VARCHAR(255),
    category_id INT
);

-- Create a category dimension table
CREATE TABLE category_dim (
    category_id INT PRIMARY KEY,
    category_name VARCHAR(255)
);

-- Create a customer dimension table
CREATE TABLE customer_dim (
    customer_id INT PRIMARY KEY,
    customer_name VARCHAR(255),
    location_id INT
);
        

4. Best Practices

• Keep dimension tables as narrow as possible.
• Use surrogate keys for foreign key relationships.
• Regularly review and optimize queries for performance.
• Document the schema and relationships clearly for future reference.

5. FAQ