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Re: data warehousing desing - to denormalize or not to denormalize - that

From: <Jared.Still_at_radisys.com>
Date: Fri, 10 May 2002 15:08:22 -0800
Message-ID: <F001.0045EBDE.20020510150822@fatcity.com>


Tim,

Don't *ever* apologize for long threads when they are full of useful content. :)

Jared

"Tim Gorman" <Tim_at_SageLogix.com>
Sent by: root_at_fatcity.com
05/10/2002 02:19 PM
Please respond to ORACLE-L  

        To:     Multiple recipients of list ORACLE-L <ORACLE-L_at_fatcity.com>
        cc: 
        Subject:        Re: data warehousing desing - to denormalize or not to denormalize - that


The distinction between a data mart and a data warehouse is not size ("Size
doesn't matter"). It just works out that way usually...

The distinction between a DM and a DW is its function within the entire decision-support strategy. A data warehouse is the consolidation point for
all data from all sources. Data marts are downstream breakouts, subsets of
that consolidated data for specific business functions, optimized for end-user access. There a situations where a data mart can exceed the data warehouse in size (usually due to different data retention requirements), but a data mart is by definition focused on one specific business topic or area whereas the contents of a data warehouse encompass the entire enterprise, across all business areas. Usually, this means the DW is larger
than any of the many possible DMs, but it is not a requirement that this be
so. Another common distinction between a data mart and a data warehouse is
political. If the accounting department ponies up money for a decision-support strategy but the marketing department does not, then you are unlikely to have anything that can be referred to as a data warehouse. Hence, the popularity of data marts...

...

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