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Because multiple cubes are expected and accepted in an OLAP environment, none of the hand-wringing caused by the need to deploy multiple semantic layers in SQL-generating environments will be encountered. Drilling across, dealing with multiple fact tables, and providing multiple configurations for bridged solutions are handled with grace, simply by producing multiple cubes and controlling who can access them.
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Cubes for Each Process, Cubes for Comparing Processes Although many OLAP tools are capable of drilling into multiple cubes simultaneously, the ability to do so is less of a concern for the OLAP BI tool. The addition of a merged cube that compares two processes fits naturally into this environment, although it may seem a kludge for SQL generators. Because each cube can be selected individually, there is also far less concern about how to deal with factless queries. The path for linking dimensions together is determined when a cube is selected as the focus of analysis. Scenarios that are factless also present no problem; the simple process of selecting the cube determines the scope of analysis. If there are multiple ways one may wish to compare data from two processes, as you saw with orders and shipments earlier in this chapter, the creation of a separate merged cube for each style of comparison eliminates any potential confusion or misuse of the data. Cube-oriented business intelligence incorporates these viewpoints naturally. The benefits of cube-oriented business intelligence are further evident as you look back at some of the other issues described earlier in this chapter. Anything that can be solved by producing a derived schema or view can also be solved by creating a new cube. Solutions that require different viewpoints for safety vs. flexibility are therefore a clean fit. For an OLAP tool that does not enforce semi-additivity, for example, the solution is obvious: produce a safe but limited cube for novices, and a flexible but more dangerous cube for experts. When cubes are created from star schemas, the various ways of dealing with a bridge can be incorporated into separate cubes. With a multi-valued dimension, it is possible to create one cube that isolates a single dimension member for each fact, and another that captures impact. In the case of collaborating salespeople, the first cube contains only the primary salesrep. This cube is safe but incapable of producing an impact report. Another cube is created that repeats an order for each salesrep. This cube can produce impact reports, but care must be taken not to double count.
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A New Concern: Cube Proliferation Because they are less scalable, cubes are usually more targeted. In addition to providing cubes for various processes, it may be necessary to produce multiple cubes for each process, leveraging the principles of derivation and aggregation from s 14 and 15 in order to maintain a performance standard. Thus, the possibility of overproliferation of cubes becomes the primary concern in the OLAP world, replacing the need to deploy multiple semantic layers in the SQL-generation world. Careful selection of the appropriate mix of cubes necessitates evaluating the various analytic requirements for required dimensionality and grain. The one-cube-per-report approach must be avoided at all costs. Each additional cube requires resources to design, build, and maintain. Unchecked, this can lead to an unmanageable environment. Each cube should be designed to support a mix of reporting needs; each new report should attempt to make use of existing cubes.
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Many multidimensional architectures provide the ability to generate and maintain cubes automatically based on information that comes from a relational schema. Cube-generating tools work especially well when the relational source is a star schema, since both technologies are used to store information based on a dimensional model. Cube generation is much like SQL generation in that it requires a watchful eye to ensure that information in the star schema is not misused. Additional attention may be required when it comes to defining hierarchies.
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