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When Struggling with Dimension Groupings
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Those new to the dimensional approach may face situations where they are not sure whether two dimensions belong in the same dimension table. If salespeople are assigned to customers, why separate customer and salesperson into different tables, as is done in Figure 6-1 Why not place them together How about making brand a dimension table and including its surrogate key in the fact table Rather than attempt to resolve these questions using the language of ER modeling, it is best to look at the ways in which the attributes relate and the ways in which they are used. For a given pair of attributes, consider the context of the relationship. Do they share a natural affinity, or can they be related in different contexts Those that tend to share a stable affinity may be stored together; those that tend to be related only in the context of events, transactions, or conditions belong in separate fact tables. When in doubt, you can consider the browsability of alternative designs.
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In a dimensional model, dimensions are grouped into tables based on natural affinity. Products and brands, for example, are related to one another prior to an order being placed. A transaction is not required to establish a relationship between these elements. In fact, a product has a brand even if there are no orders for it. More importantly, these attributes can only be related in one way, or one context.
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On the other hand, some elements are only related based on transactions or activities. Salespeople and customers, for example, are brought together only when transactions, such as orders, occur. These attributes, therefore, belong in separate tables; their relationships will be captured in the fact table. This allows customers and salespeople to have numerous interactions, perhaps even in different pairings. The relationships are defined by the transactions. TIP When two dimension attributes share a natural affinity, and are only related in one context, they belong in the same dimension table. When their relationships are determined by transactions or activities, and they can occur in multiple contexts, they should be placed in separate dimension tables. Looking deeper, you may also realize that salespeople and customers may be related in multiple contexts. For example, salespeople may be assigned to customers, they may take calls from customers, and they may visit customers. Each of these relationships flows from a different process and can be thought of as an activity or transaction: an assignment of a salesperson to a customer, a phone call being made, or a visit to a customer site. These various associations can be captured through a series of fact tables, each representing a different process. As described in 5, these relationship chains may offer rich analytic possibilities when used individually or compared.
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If you are not sure whether two attributes belong together in a dimension table, consider how they will be used. Recall from 1 that a query focused on the values within a dimension is called a browse query. Natural affinities like product and brand can be separated from transactional relationships like customers and salespeople by evaluating browsability. Would someone want to browse the values of these attributes together Placing them in separate dimensions would prevent this. The separation of product and brand, as shown in Figure 6-2, destroys the browsability of these attributes. In this configuration, it is only possible to study the intersection of products and brands in the context of orders. If there is no order for a particular product, it will not be possible to identify its brand. It makes more sense to place these attributes in a single table. Salespeople and customers, on the other hand, have a relationship only when transactions occur. This relationship may also be more volatile. A given customer may speak with a different salesperson each time an order is placed. In this case, the transaction defines the relationship and is embodied in the fact table. The astute reader may observe that in a situation where a business assigns salespeople to specific customers, it may be possible to merge their attributes. This would allow users to browse the list of customers assigned to a particular salesperson; however, salespeople and customers may engage in other activities with various contexts, as noted earlier. Salespeople take calls from customers, process returns, and so forth. Clearly, the business considers salespeople and customers to be two separate things. If it is necessary to track the assignment of customers to salespeople, a factless fact table may be called for. This technique will be discussed in 12, Factless Fact Tables.
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