Building the Data Warehouse

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■    Primitive data supports the clerical function. Derived data supports the managerial function.


It is a wonder that the information processing community ever thought that both primitive and derived data would fit and peacefully coexist in a single database. In fact, primitive data and derived data are so different that they do not reside in the same database or even the same environment.

The Architected Environment


The natural extension of the split in data caused by the difference between primitive and derived data is shown in Figure 1.10.


levels of the architecture




atomic/data


warehouse





Figure 1.10 Although it is not apparent at first glance, there is very little redundancy of data across the architected environment.

There are four levels of data in the architected environment—the operational level, the atomic or the data warehouse level, the departmental (or the data mart level), and the individual level. These different levels of data are the basis of a larger architecture called the corporate information factory. The operational level of data holds application-oriented primitive data only and primarily serves the high-performance transaction-processing community. The data-warehouse level of data holds integrated, historical primitive data that cannot be updated. In addition, some derived data is found there. The departmental/ data mart level of data contains derived data almost exclusively. The depart-mental/data mart level of data is shaped by end-user requirements into a form specifically suited to the needs of the department. And the individual level of data is where much heuristic analysis is done.

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