Building the Data Warehouse

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■■ Customer name and ID ■■ Customer volume—high/low ■■ Customer profitability—high/low


■■ Customer frequency of activity—very frequent/very infrequent ■■ Customer likes/dislikes (fast cars, beautiful women, single malt scotch)


Each of the categories of information found in the profile record is created from the examination and analysis of the many detailed records found in the data warehouse. There is then a very fundamental difference between the data found in the data warehouse and the profile data found in the class IV ODS.


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Fig 3.57 The data warehouse supports a class IV ODS.



Summary


The design of the data warehouse begins with the data model. The corporate data model is used for the design of the operational environment, and a variation of the corporate data model is used for the data warehouse. The data warehouse is constructed in an iterative fashion. Requirements for the data warehouse cannot be known a priori. The construction of the data warehouse is under a development life cycle completely different from that of classical operational systems.


The primary concern of the data warehouse developer is managing volume. To that end, granularity and partitioning of data are the two most important issues of database design. There are, however, many other physical design issues, most of which center around the efficiency of access to data.


The data warehouse is fed data as it passes from the legacy operational environment. Data goes through a complex process of conversion, reformatting, and integration as it passes from the legacy operational environment into the data warehouse environment. Often, as data passes into the data warehouse environment there is a shift of time. In some cases, the operational data has no timestamping, and in other cases, the level of granularity of the operational data needs to be adjusted.

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