Data Architecture Patterns

Architecture Selection Decision Tree

Structured only -> Data Warehouse | Mixed + SQL analytics -> Data Lakehouse | Mixed + ML-primary -> Data Lake | Large org + autonomous domains -> Data Mesh

Data Warehouse

Schema: structured, schema-on-write | Data: tables, rows, columns | Governance: centralized | Query: SQL analytics, BI | Architecture: centralized single source of truth

Schema Patterns

Star Schema: Central fact table (measures) surrounded by denormalized dimension tables. Best for BI dashboards, standard reporting.

Snowflake Schema: Normalized dimensions (dimensions reference other dimensions). Reduces storage, increases JOIN complexity. Best when storage cost matters more than query speed.

Kimball vs Inmon

Kimball (Bottom-Up): Build data marts first, integrate later | Star schema, business-process driven | Faster initial delivery | Best for quick wins, department-level analytics