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Using Generic Attributes
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A dimensional design can accommodate heterogeneous attributes through the use of generic columns. For a given row, what is held in each column is determined by its type. Auxiliary tables can be used to map the purpose of each column to each type. This approach is very flexible for storing information but less nimble when it comes to querying the information. This may seem contrary to the purpose of a dimensional design, but it can be powerful when all interaction will take place through a custom-developed front-end application. Though not a common feature of a dimensional design, it may be worth considering in rare situations.
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Generic Attributes
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The use of generic attributes seeks to capture the diversity of various types using a single set of columns. In a dimension table, a set of columns describing core attributes is supplemented by a set of multipurpose columns, the purpose of which will vary by type. For example, a business might choose to handle location data in this manner. There may be several types of facilities factories, warehouses, stores, and offices. Each has a
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FACILITY facility_key facility_type name attribute_1 attribute_2 attribute_3 attribute_4
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FACILITY_ ATTRIBUTE_ DEFINITIONS facility_type attribute_name attribute_defintion
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FACILITY_ATTRIBUTE_DEFINITIONS facility_ type Warehouse Warehouse Warehouse Warehouse Factory Factory Factory Factory attribute_ name attribute_1 attribute_2 attribute_3 attribute_4 attribute_1 attribute_2 attribute_3 attribute_4 attribute_definition Warehouse Manager Distribution Region Facilities for Perishables Number of Loading Docks Foreman Factory Type Clean Room Entrances
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Figure 13-7 A dimension table with generic attributes
name, an attribute that identifies the individual in charge, and several type-specific characteristics. Figure 13-7 illustrates a facility dimension table that abstracts these type-specific attributes into a set of generic attributes. For any given row in the facility table, the meaning of each generic column is determined by the facility type. The generic column names are mapped to type-specific definitions in an auxiliary table called facility_attribute_definitions. Consulting this table, you can identify what each column indicates on a type-by-type basis. For the facility type Warehouse, for example, attribute_3 indicates whether the facility has the capability to stock perishable goods. For factories, this same column indicates whether the facility has a clean room. This design is very flexible when it comes to storing information, permitting the storage of customized attributes for a large number of types, all within a single table. Some types may make use of all of the generic attributes, while others make use of some of them. As long as there are enough generic columns of the appropriate data types, it is possible to accommodate any type. A similar technique can be used to capture variation within a fact table.
13 Type-Specific Stars 321
Using a Generic Design
Though very flexible for storing information, a generic design is less flexible when it comes to retrieving information. Because column names are generically defined, the construction of queries requires referring to information on column content. Query results, as well, will need to be repackaged with decoded attribute labels. These activities are not directly supported by standard query and reporting software. For example, suppose the dimension table in Figure 13-7 is part of a star describing inventory levels. A report is needed that provides inventory levels for warehouses that have facilities for perishable goods, and the results will be grouped by region. Construction of a query to fetch this information will require using reference data to identify which column indicates whether the warehouse has the capability to store perishables. This turns out to be attribute_3, which can be used to constrain the query, as in:
where facility.attribute_3 = 'has Perishable Storage Facilities'
Grouping the results by region also requires identification of the appropriate attribute. In this case, attribute_2 contains the needed information:
GrOUP BY facility.attribute_2
Packaged query and reporting software does not normally perform this value-based translation of attribute names. Whether intended for developer use or end-user use, most tools are based on a paradigm where each attribute in a schema has a single name or business definition. Development of a custom application that is aware of the supplemental information, however, can lead to some very compelling analytic applications. A custom-built application can leverage the attribute definition information to adapt column headers or field names dynamically, based on attribute type. Some OLAP products also have the capability to do this. Such an application can guide users or developers through the process of constructing queries, adapting attribute definitions as specific types are selected. This kind of application may also perform attribute translation on query result sets, even when more than one type is included. For example, an application can be coded to accept result sets for warehouses and factories, each of which contains attribute_1 through attribute_4, and place them in separate report sections with the appropriate labels. Such a tool might also support dynamic attribute labeling as a user drills into data. TIP The use of generic attributes is usually undesirable because they render the data less accessible. However, in combination with a custom-developed application, they can contribute to a compelling analytic experience. A hybrid approach enables this kind of application, while at the same time making the data accessible to more traditional query and reporting software. Core and custom fact tables are designed for standard queries and reports. In addition, generic attributes are added to the core tables. These will be used by specialized reports or applications that have been developed to be aware of the abstraction layer. These columns will only be used by this application; they are hidden from standard query and reporting software.
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