5.1. Working with the Dimension Wizard

Dimensions help you to define the structure of your cube so as to facilitate effective data analysis. Specifically, dimensions provide you with the capability of slicing data within a cube, and these dimensions can be built from one or more dimension tables. As you learned in Chapter 1, your data warehouse can be designed as a star or snowflake schema. In a star schema, dimensions are created from single tables that are joined to a fact table. In a snowflake schema, two or more joined dimension tables are used to create dimensions where one of the tables is joined to the fact table. You create both of these dimension types in this chapter.

You also learned in Chapters 1 and 3 that each dimension contains objects called hierarchies. In Analysis Services 2005 you have two types of hierarchies to contend with: the attribute hierarchy, which corresponds to a single column in a relational table, and multilevel hierarchies, which are derived from two or more attribute hierarchies where each attribute is a level in the multi-level hierarchy. A typical example of an attribute hierarchy would be zip code in a Dim Geography dimension, and a typical example for a multilevel hierarchy would be Country-State-City-Zip Code also in a Geography dimension. In everyday discussions of multilevel hierarchies, most people leave off the "multilevel" and just call them "hierarchies."

For the exercises in this chapter, you use the project you designed in Chapter ...

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