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Using an Attribute Bridge
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An attribute bridge can be used to model multi-valued attributes in a dimension table. Technically speaking, these attributes will not be in the dimension table itself. Instead, they are placed in an outrigger. A bridge associates the values, providing a flexible and
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Figure 9-9 Simplifying a multivalued industry attribute
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TIP When faced with a multi-valued attribute, evaluate the possibility of simplifying it into a fixed number of single-valued attributes. If the repeating attributes will not be used to filter or group query results, this is the simplest option.
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powerful solution. With this power comes risk; as with the dimension bridge, the possibility of double-counting exists.
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A multi-valued attribute can be supported using an attribute bridge table, which works in much the same way as the dimension bridge in the previous section. This time, instead of placing the bridge between fact table and dimension table, the bridge will be placed between the dimension table and an outrigger. Here s how it works: The multi-valued attributes are not stored in the dimension table. Instead, they are placed in a separate table with its own surrogate key. This table will act as an outrigger. A bridge table is set up with two columns: a group_key and a second column referring to the outrigger. When a dimension row refers to a specific combination of values in the outrigger, a group is set up for those values in the bridge table. The dimension table and the bridge can be joined using the group_key; the bridge table is joined to the outrigger in turn. Once again, this solution is best understood via an example. The design in Figure 9-10 uses a group table to capture multiple industries for each customer. Industry attributes are not stored in the customer dimension; instead, they are located in an outrigger table called industry. Customers and industries share a many-to-many relationship, so it is not possible to design a solution where these tables are joined directly. Instead, a group table is used to bridge the relationship between a given customer and its industry designations. To understand the workings of this solution, look at the instance diagrams in the lower half of the figure. You may recall that Company C participates in two industries: manufacturing
ORDER_FACTS day_key customer_key product_key salesrep_key . . . order_dollars . . . CUSTOMER customer_key customer_id customer_name industry_group_key . . . INDUSTRY_GROUP industry_group_key industry_key primary_industry
INDUSTRY industry_key industry_code industry_name . . .
CUSTOMER customer_ customer_ customer_ key id name 2012 C771 Company C industry_ group_key 100
INDUSTRY_GROUP industry_ industry_ primary_ group_key key industry 100 100 901 902 Primary Not Primary
INDUSTRY industry_ key 901 902 industry_ code B404 B492 industry_ name Manufacturing Services
Figure 9-10 An attribute bridge table
9 Multi-Valued Dimensions and Bridges 211
and services. To represent this state of affairs, a group is set up in the industry_group table with an industry_group_key value of 100. The table for industry_group_key 100 has two rows; one has an industry_key value of 901, the other has an industry_key value of 902. These refer to manufacturing and services in the industry table. In the company table, the row for Company C simply references the group. This approach provides maximum analytic flexibility. Unlike the flattened solution, it can accommodate groups of any size. In addition, it is easy to use an industry name to filter or group query results, simply by joining together the customer, industry_group, and industry tables. As before, the presence of the bridge will require additional work when loading the schema. The ETL process must detect and manage groupings. Groups with one member will be necessary for companies that have only one industry. TIP Compared to a solution that simplifies multi-valued attributes, using a bridge table offers increased flexibility and simplifies reporting challenges. Just as the benefits of the attribute bridge table mirror those of the dimension bridge table, so do the other impacts. It will be necessary to avoid double-counting and to consider the ramifications of changed data; it may also be necessary to work around the limitations of software products that will not tolerate a many-to-many relationship.
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