barcode vb.net 2010 Multi-Valued Dimensions and Bridges in Software

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CHAPTER
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Multi-Valued Dimensions and Bridges
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A crucial feature of every example in the first eight chapters of this book has gone unmentioned. Each and every dimension attribute has participated in a simple one-tomany relationship with every fact. This essential characteristic has allowed dimensions to be arranged around fact tables in the neat and powerful star configuration with which you are now familiar. The real world, of course, is not always neat. Real-world complexity sometimes makes it impossible to model a process in this manner. This chapter explores two such challenges: Multi-valued dimensions occur when a fact table row may need to refer to more than one row in a dimension table. Multi-valued attributes occur when a dimension row needs to capture multiple values for a single attribute. In both cases, a star configuration simply will not support the true complexities of the process. The solution to both these challenges introduces a new kind of table, called a bridge. Think of a bridge table as a double-edged sword. It provides the ultimate power and flexibility, enabling a wide variety of analytic possibilities. This power comes with significant costs, and chief among these is risk. Put simply, the presence of a bridge increases the possibility that the schema can be misused, producing inaccurate results. The specter of this risk is so great that many shops will refuse to consider using a bridge at all. This rejection, however, may severely cripple the analytic capabilities of a dimensional solution. Alternatives are available, but their analytic flexibility is limited. Before dismissing the bridge out of hand, you and your colleagues must understand it fully. Only then can you make an informed decision that balances the power and risk of the various options. This discussion will begin by calling to the fore the previously implied one-to-many relationship of most dimension tables to the facts. The challenges of multi-valued dimension tables and multi-valued dimension attributes will then be studied in turn. You will learn the
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PART III
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Dimension Design
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limitations of trying to address these challenges with a standard design, how a bridge can solve the problem, and the potential consequences. You will also be provided with techniques to mitigate such consequences, and challenged to think about slow-change processing in a new light.
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Until now, each star schema you have seen in this book has been characterized by a distinctive and important feature. Every fact has been related to exactly one instance value of each dimension. In an order_facts table, for example, each order is related to exactly one product. Looking at these relationships from the opposite direction, it has also been true that each dimension value may be related to one or more fact table rows. Putting these characteristics together, we say that dimensions and facts have a one-tomany relationship. A one-to-many relationship is sometimes called other names, such as master detail or parent child. The fact table is sometimes referred to as a dependent entity, since its definition depends on the primary keys of other tables. These terms all indicate the same thing: each fact is related to exactly one row in each dimension table. Following the conventions of entity-relationship modeling, these standard relationships might be illustrated in a manner similar to the diagram in Figure 9-1. The crow s feet at the end of a line indicate the many side of the relationship. This style of diagramming is not normally used for dimensional modeling but will be useful for some of the issues explored in this chapter and the next. If you are familiar with IDEF modeling, you may be accustomed to a similar diagramming style in which solid circles replace the crow s feet. In the example, a product may be related to zero or more order_facts, and each order_ facts row must be related to exactly one product. (In the diagram, a solid line emanating from a table indicates a mandatory relationship, and a dotted line indicates an optional one, but we will not make further use of this convention.) The same holds true for each of the other dimension tables in the diagram. Diagrams in this chapter will not illustrate optionality (dotted lines) but some will indicate cardinality (crow s feet). Because each fact table row relates to exactly one row in each dimension table, we can make a similar observation about the relationship between a fact table row and each dimension column. For example, if one of the columns of the product table is brand_name, then we can say that each row of order_facts is related to exactly one brand_name.
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