Two competing philosophies for building data warehouses: Bill Inmon’s top-down approach (enterprise warehouse first, then data marts) vs. Ralph Kimball’s bottom-up approach (data marts first, then conformed dimensions). This distinction maps directly to the Dependent vs. Independent data mart types.
The fundamental disagreement is where to start: build the complete enterprise warehouse first (Inmon) or build department-level data marts first and integrate them later (Kimball). Inmon prioritizes data consistency; Kimball prioritizes speed to value.
| Dimension | Dependent (Inmon) | Independent (Kimball) | Hybrid |
|---|---|---|---|
| Starting point | Central enterprise warehouse | Departmental data marts | Both simultaneously |
| Data flow | Sources → DWH → Data Marts | Sources → Data Marts → (DWH later) | Sources → DWH → Marts AND Sources → Marts |
| Data consistency | Guaranteed (single source of truth) | Risk of inconsistency (data silos) | Moderate (central hub + direct paths) |
| Time to value | Slow (warehouse first) | Fast (marts first) | Moderate |
| Cost | High upfront | Lower upfront, may increase during integration | Variable |
| Best for | Large organizations (MNCs) | Small organizations, startups | Organizations with mixed needs |
| Integration risk | Low (integration done first) | High (integration deferred) | Moderate |
- Large organization with centralized operations
- Budget allows for upfront enterprise warehouse investment
- Data consistency is the highest priority
- Long-term analytical strategy exists
- Small organization or startup
- Limited budget, need quick wins
- Departments need analytical capability immediately
- Willing to accept integration risk for speed
- Organization has both enterprise-wide and department-specific needs
- Some departments need immediate capability while central warehouse is being built
- Flexibility is more important than architectural purity
The Inmon vs. Kimball debate is often framed as a binary choice, but in practice, most successful warehouses evolve from Kimball to Inmon. Organizations start with independent data marts (quick wins), then gradually build a central warehouse as inconsistencies become painful. The hybrid model is the most realistic path for growing companies — it acknowledges that architectural purity must be balanced against business urgency.
- Data Mart Types — the three types embody these approaches
- DWH Server Models — server architecture follows the chosen approach
- Integrated DWH — Inmon’s approach maximizes integration
- DWH Evolution — both approaches emerged in the 1990s OLAP era
- Three-Tier DWH Architecture — both approaches implement the three tiers differently
- OLTP vs OLAP — both approaches serve the OLAP side of the split