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However, comparing facts from multiple stars is the basis for many important and powerful reports. This kind of limitation may be overcome by enhancing the schema design. A derived star, or cube, may be added that performs the activity the query generator cannot. The inability to drill across, for example, can be addressed by adding a merged fact table, as discussed later in this chapter. The burden is essentially shifted from the business intelligence tool to the ETL process. Developers are frequently cautioned not to modify a database design based on the capabilities of a particular tool. The capabilities of the front-end tools, however, are usually beyond the control of the schema designers. Failure to adapt may result in the loss of important functionality. Dogmatic adherence to theoretical principles can severely reduce the value of the data warehouse. In the case of a derived table, however, this is a moot point. The addition of a derived schema in no way compromises a dimensional design. It is completely within the realm of best practices, as discussed in 14. A properly designed derived schema is consistent with and conforms to the original dimensional data structures. It may be added to the model for a variety of reasons, including the capability of tools to generate queries, the performance of the original schema, and the ease of use. Some of these factors may come into play even if the front-end tool is capable of formulating desired queries.

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SQL generators can also pose a second kind of problem: often, they are able to generate queries that are not desired because the result is inaccurate For example, most business intelligence tools will happily generate a query that aggregates a semi-additive fact, such as a bank account balance, across an inappropriate dimension, such as days This may not be a concern if well-trained developers are using the tool but can have devastating effects if the tool is made available to novices In cases like these, derived schemas may again come to the rescue By making use of standard dimensional design techniques, it is often possible to provide a derived schema that avoids some of the potential dangers inherent in dimensional designs In the case of the semi-additive account balance, for example, a sliced fact table can be created that provides access only to the current period s balance.

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Novice users can be limited to this view of data While less flexible, it keeps them out of trouble Power users and developers can be provided access to the original fact table, and trusted not to sum the account balance across days Note that this particular solution may be achieved without actually building the derived star It can be implemented by creating database views, or even through the use of features of the business intelligence tool itself Regardless of its physical implementation, however, it establishes a derived star at the logical level Solutions like this often require that the data warehouse team recalibrate their expectations of the business intelligence tool It may be necessary to create multiple semantic layers one for the novices, who can view current account status, and one for the experts, who can view daily account status.

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