Chapter 14

Agile Integration Layers with Hyper Normalization

Data warehouses built using traditional modeling techniques are expensive to adapt for new business requirements, but EDW team leaders can avoid this predicament by switching to “ensemble data modeling” for their data integration layers. In all three schools of ensemble modeling, separate data tables are created for a company’s business keys, the relationships between them, and their attributes. Ensemble modeling results in data schemas with more tables than standard data normalization, so we can say that it “hyper normalizes” a data warehouse’s integration layer. Even with these additional tables, however, the ETL programming for an EDW project is greatly reduced because teams need ...

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