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Fact-Dimension Pattern

Core pattern for modeling fact and dimension tables.

Overview​

The fact-dimension pattern is the foundation of dimensional modeling. Facts are events/transactions, dimensions are descriptive attributes.

Fact Tables​

Facts represent business events or transactions.

Characteristics:

  • Higher cost (100)
  • Many rows
  • Contain measures (aggregatable metrics)
  • Foreign keys to dimensions

Example:

name: Orders
cost: 100

fields:
  - type: measure
    name: Total Revenue
    expression:
      sql: sum(amount)

Dimension Tables​

Dimensions provide context for facts.

Characteristics:

  • Lower cost (10)
  • Fewer rows
  • Contain dimensions (categorical fields)
  • Primary keys

Example:

name: Customer
cost: 10

fields:
  - type: dimension
    name: Customer ID
    expression:
      primary_key: true
      sql: customer_id

Relationships​

Facts join to dimensions:

orders_customer:
  left: Orders
  right: Customer
  sql: left.customer_id = right.id
  cardinality: many_to_one

Best Practices​

  1. Fact cost: 100 - Higher cost
  2. Dimension cost: 10 - Lower cost
  3. Many-to-one - Fact to dimension
  4. Primary keys - On dimensions
  5. Measures in facts - Aggregatable metrics

Next Steps​