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The relationship between the data warehouse and the data mart. The structure of the data found in the data mart is shaped by the particular requirements of the department. The finance department will have one structure for its data mart, the sales department will have another structure for its data mart, and the marketing department will have another data structure for its data mart. All of their structures will be fed from the granular data found in the data warehouse. The data structure found in any given data mart is different from the data structure for any other data mart. For example, the sales data mart data structure will be different from the marketing data mart data. The data mart structures are typically known as star joins and contain fact tables and dimensions. The data mart structures are typically known as multidimensional structures and are served by OLAP technology. Because there is a different data structure for each data mart, making any data mart into a data warehouse doesn t make sense. When a data mart star join is made into a data warehouse, the data warehouse is optimal for one data mart and its users and is not optimal (or really usable) for anyone else. Data marts produce structures that are not reusable except by someone operating in the department that is optimized. Data mart data structures in general, across the enterprise are not reusable, are not flexible, are not useful as a foundation for reconciliation, and are not standing ready for a new set of unknown requirements. But the normalized granular data found in a data warehouse is indeed all of those things.

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P1: KAO WY050-13 WY050-Ulick-v4 September 19, 2004 12:6

the model provides optimal solutions that do not satisfy the posed constraints, something is obviously wrong It can be concluded that thorough Model Veri cation (see Figure 84) is required that is, verifying that the model and the applied solution techniques are correct Nevertheless, even if the model works all right technically, the Model Solution need not be valid in practice Nonrealistic parameter values or other fatal deviations from reality may result in model outcomes that are not usable in practice Since a model always describes only certain parts of reality; in an abstract way, this so-called Model Validation (see Figure 84) can be a serious hurdle In this stage, feedback from the planners is indispensable, since the solutions generated by the model should be acceptable to the planners.

Many phenomena follow the Rayleigh distribution and for some the distribution is required in terms of power ratio or X = r2/2r2. Substituting we have p r dr exp X d X (44)

Usually a rst evaluation of the obtained solutions by the planners leads to new alternatives or to new constraints that are to be taken into account After several iterations, this process may lead to a model and solutions that are indeed acceptable After one has obtained an initial solution that seems to be acceptable in practice, a next useful step is to carry out an extensive sensitivity analysis This is especially the case if parts of the input data are uncertain or only approximately known, or if several scenarios with different input values need to be discerned To that end, one may study the response of the model outcomes to (small) changes in the data (see also Figure 85) Somewhat related to sensitivity analysis is the notion of a robust solution to an optimization problem.

wired components can be Java objects that you have written for the application, or one of the many prefabricated components in the Spring API library (or a component from a third-party vendor, such as a transaction manager from Hibernate). It is of paramount importance, then, to understand how components instantiation and wiring work in Spring. There is no better way to show how Spring object wiring works than through an actual example. The Spring framework works with modularized applications. The first step is to create such an application. The next section shows you how to start with an all-in-one application and break it down into components. Then you can see how Spring adds value by flexibly wiring together the components.