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A professional-level summary covering key definitions, frameworks, and exam-relevant points.
Data Warehouse Architecture Comparison
| Aspect | Inmon (Top-Down) | Kimball (Bottom-Up) |
|---|---|---|
| Starting point | Enterprise data warehouse | Individual data marts |
| Schema design | Normalised (3NF) | Dimensional (star/snowflake) |
| Time to value | Longer (months to years) | Faster (weeks to months) |
| Integration | Built-in from the start | Achieved through the bus architecture |
| Complexity | Higher upfront | Lower upfront, higher over time |
| Best for | Large enterprises with long-term vision | Organisations needing quick wins |
Slowly Changing Dimensions (SCD Types)
| SCD Type | Approach | History Preserved? |
|---|---|---|
| Type 0 | Never change the value | N/A (fixed values only) |
| Type 1 | Overwrite the old value | No (history lost) |
| Type 2 | Add a new row with effective dates | Yes (full history) |
| Type 3 | Add a new column for the previous value | Partial (one previous value) |
| Type 4 | Use a separate history table | Yes (in separate table) |
| Type 6 | Combination of Types 1, 2, and 3 | Yes (hybrid approach) |
CDMP Exam Relevance
Data Warehousing & Business Intelligence is one of the highest-weighted CDMP knowledge areas (10%). Key exam topics include: Kimball vs Inmon approaches and their characteristics, star vs snowflake schema differences, SCD types and when to use each, the ETL process and its role in data warehousing, and the four characteristics of Inmon's data warehouse definition (subject-oriented, integrated, non-volatile, time-variant).
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