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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.

that will establish the route to the final destination. Deciding the functionality of the target destination is essential. To be effective, it must be captured and depicted in detail. In today s software development environment, we speak of objects as things that encapsulate attributes and operations. Before we proceed to the modeling standards being used today by software architects, let's begin with some basic definitions of object programming and its intending analysis, design, and life cycle.

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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..

Object-oriented programming (OOP) is the methodology used for programming classes based on defined and cooperating objects. OOP is based on objects rather than procedural actions, data rather than logic. In days past, a program had been viewed as a logical procedure that used input data to process and produce output data. Object-oriented programming focuses on the objects we want to manipulate rather than the logic required to manipulate them. Object examples range from human beings (described by name, address, and so forth) to inanimate objects whose properties can be described and managed, such as the controls on your computer desktop buttons, scroll bars, and so on. Step one in OOP is to identify the objects to be manipulated and their relationships with each other. That is the essence of modeling. Once you ve identified an object, you generalize it as a class of objects and define the kind of data it contains and logic that can manipulate it. The logic is known as methods. A real instance of a class is called an object or an instance of a class. The object or class instance is executed on the computer. Its methods provide computer instructions, and the class object characteristics provide relevant data. You communicate with objects and they communicate with each other with defined interfaces called messages. The concepts and rules used in OOP provide these important benefits:

The XSD is generated with temporary URI (tempuri.org) namespace references. You can replace them with your own namespaces:

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.

objects that share some or all of the main class characteristics. This is known as inheritance, and it is a property of OOP that facilitates thorough data analysis, reduces development time, and ensures more accurate coding.

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