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Figure 7-1 Adding dimensional detail
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If you have a different notion of what drilling is, chances are it has been influenced by software products you have used. Developers of query and reporting tools describe a variety of different activities with the term drill, often embellishing it with various prefixes and suffixes, for example, drill-up, drill-down, drill-though, and skip-drill. You may be familiar with others as well. The drill feature of a given software product is usually a special case of the concept just defined. Some tools reserve the term for activities that will have an instantaneous response. If moving from order dollars by category to order dollars by category and month requires a new SQL query, these products would not describe the activity as drilling. Other tools incorporate the notion of focusing on an instance value. For example, breaking out the specific category boxes by month, rather than all categories, might be referred to as drilling into boxes. Still other tools require that a drill path be defined in advance of drilling. Finally, for many tools, the concept of drilling is intertwined with another concept, that of attribute hierarchies. For these products, we drill from years to quarters to months to days or from categories to brands to products. There is nothing wrong with any of these variations on the theme. Each technique represents a valid form of analysis. Keep in mind that features like these should not serve as the sole roadmap for the exploration of data. If users can only follow an established hierarchy, the results will be frustratingly limited.
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Attribute hierarchies offer a natural way to organize facts at successively deeper levels of detail. Users understand them intuitively, and drilling through a hierarchy may closely match the way many users prefer to break down key business measurements. Other ways exist to make sense of information, however. Some cross attribute hierarchies, some don t involve hierarchies at all, and some involve hierarchies of a very different sort. Still, many business intelligence tools require the definition of attribute hierarchies to support their drill-down feature. If yours does, it will be important to document the attribute hierarchies in each dimension table. This information may also prove useful when planning conformance, or designing and building cubes or aggregates.
The Attribute Hierarchy
Many dimensions can be understood as a hierarchy of attributes, participating in successive master detail relationships. The bottom of such a hierarchy represents the lowest level of detail described by the dimension table, while the top represents the highest level of summarization. Each level may have a set of attributes and participates in a parent child relationship with the level beneath it. The attributes in a product dimension table, for example, may form a simple hierarchy. Products fall within brands, and brands fall within categories. Each of these levels has a set of associated attributes, and they can be organized as a set of successive master detail relationships, as illustrated in Figure 7-2. Attributes of the product table are grouped into levels, moving from the most highly summarized view of product at the top, down through
Part III
PART III
Dimension Design
Product Dimension Table PRODUCT product_key sku product_name product_color brand_code brand_name brand_manager category_code category_name Most summarized
Attribute Hierarchy ALL PRODUCTS
CATEGORY category_code category_name
BRAND brand_code brand_name brand_manager
PRODUCT sku product_name product_color
Most detailed
Figure 7-2 An attribute hierarchy in the product table
successive levels of detail. Crows-feet are used to indicate the many ends of each one-tomany relationship. At the very top of the hierarchy is the level called all products. This level contains no attributes; it is added for convenience and represents a complete summarization of the product dimension. At the very bottom of the hierarchy is the level called product. It represents the most detailed level in the hierarchy. The product hierarchy can be represented in nondiagrammatic format using the following shorthand: All Products (1) Categories (25) Brands (650) Products (8000) Numbers have been added to represent the cardinality, or number of instances, at each level in the hierarchy. The highest level of summarization, all products, is again added for convenience. It represents a complete summarization of the product dimension; studying a fact by all products results in a single row of data. There are 25 categories, 650 brands, and 8000 total products. Don t fall into the trap of assuming each category has 26 brands. The actual values may exhibit an uneven distribution or skew; one category, for example, may contain a much larger percentage of the brands than any of the others.
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