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SmartData Collective > Big Data > Data Warehousing > Data warehouse architecture that’s too narrowly focused
Business IntelligenceData Warehousing

Data warehouse architecture that’s too narrowly focused

RickSherman
RickSherman
1 Min Read
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In my DM Review 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…

Dmreview_11

In my DM Review 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.

More Read

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“Predictive analytics allows your organization to learn from its collective experience and puts this…”

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.

>>> Read the rest of my article "Too Narrowly Focused" on the DM Review website.


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