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Sometimes, there appear to be no facts to describe an important business activity. You may be able to define the process, identify fact table grain, and specify numerous dimensions, but find yourself unable to identify any facts. This should not stop you from designing a star schema to track the process. In this situation, you can design a factless fact table. Although it contains no facts, it measures the business activity. Analysis is conducted by counting rows in the fact table. Adding a fact that is always populated with the value 1 can simplify query writing but is not required. Sometimes, if you look closely enough, you may find a fact after all, but a factless design is perfectly acceptable.

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For many business processes, the only measurement is the occurrence of events or activities. There are no dollar amounts to be aggregated, no quantities to be summed, no balances to be averaged. Activities are taking place, however sometimes at a breakneck pace. Businesses measure this kind of process simply by counting the activities. Examples of this kind of activity abound. For example: The processing of documents (like contracts or applications) is measured by counting how many are handled by day across a variety of dimensions, including activity (received, reviewed, rejected, etc.), customer, and person doing the processing. Customer support is measured by counting the number of service requests opened, closed, or otherwise processed by representative, customer, product, and problem ticket. Advertisers count the number of impressions, or exposures to an advertisement, across a variety of dimensions. Web site usage is measured by counting page views or interface clicks. Schools and businesses track attendance or absence. You may hear dimensional modelers say no measurements exist for these processes. This is not entirely true: counts are legitimate and important measurements. It just so happens it is not necessary to store a fact to support counting. The fact table may be factless, but the process is measured.

When the only thing measured is the occurrence of events, it is possible to design a factless fact table. Like any other fact table, it has a grain. The grain is defined such that each row represents an individual activity. Every row contains foreign keys that refer to the dimensional context of the activity, and perhaps one or more degenerate dimensions. Although no facts are explicitly recorded, the mere existence of a row in this table constitutes a measurement: one activity occurred.

While salaries, bonuses, and long-term incentives are open to scrutiny by the public, boards and management can engage in stealth compensation by providing lucrative enhancements to.

10 years of rallies, 1994 2004

TIP Activities with no associated facts can be tracked in a factless fact table. Each row is a set of foreign keys that describes the dimensionality of the event. The presence of a row constitutes a measurement. Customer contact can be measured in this manner. Suppose that a business wants to measure the amount of contact that takes place with customers. Understanding this may help it fine-tune various activities, avoiding situations where customers are contacted too frequently or too infrequently. In this example, assume there are two channels for customer contact: e-mail and telephone. A given contact may be initiated by the customer (inbound) or by the business (outbound). Some outbound contacts may be automated, such as an e-mail newsletter, while others are not. This activity is measured by the factless fact table in Figure 12-1. The fact table contact_facts measures customer contact activities. Its grain is defined as one row for each contact event with a customer. Each row includes foreign keys that refer to dimension tables, and nothing else. The dimensions include the date and time of the contact, the customer contacted, and the type of contact. Examples of contact types are illustrated beneath the schema diagram.

CONTACT_TYPE contact_ type_key 100 101 102 103 104 105 106 contact_ channel E-Mail E-Mail E-Mail E-Mail Telephone Telephone Telephone automated Automated Automated Not Automated Not Automated Not Automated Not Automated Not Automated direction Outbound Outbound Inbound Outbound Outbound Inbound Outbound description Weekly Coupons eNews Mailing Tech Support Tech Support Promotional Offer Tech Support Tech Support

Figure 12-1

14,000 Dow Industrial Average Dow Transportation Average S&P 500 Index Nasdaq Index (10 years of rallies) Early Santa 5000 4500 4000 3500 3000 2500 6,000 2000 1500 1000 2,000 Transportation Average 500 0

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