In my recent columns, “The Accidental Architecture” and “Recovering from the Accidental Architecture,” I discussed whether people understood the “why” of best practices, such as dimensional modeling and hub-and-spoke architecture. In “Don’t Stop at How, Learn Why,” I discussed the most common problems when people are too hub myopic, cloning their source systems or assuming the hub will support all reporting and analytic needs.

There are also dangers with being too spoke-centric (with data marts or cubes) and failing to establish the hub, or data warehouse (DW), as the enterprise data backbone.

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