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A query can be returned in the form of an attached file:

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.

See ResourceBundle a little later in this chapter for more advanced uses of properties for localization.

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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.

As mentioned, a locale is a way of identifying and using the exact language and cultural settings for a particular session or user. In Java, a locale is identified by one, two, and occasionally three elements:

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

This is the basic identifier for a locale. It contains a valid International Standards Organization, ISO 639, two-letter language code. Examples are en for English and es for Spanish. (A complete list of two-letter language codes can be found at http://ftp.ics.uci.edu/pub/ietf/http/related/iso639.txt.) This is a country code. It contains a valid ISO 3166 twoletter country code. Examples are GB for United Kingdom, CO for Colombia, and US for United States. (A complete list can be found at http://www.chemie. fu-berlin.de/diverse/doc/ISO_3166.html or http://std.dkuug.dk/i18n/ISO_3166.)

Figure 12-1

This element is less frequently specified. It is used for creating locales with vendor- or browser-specific code. Examples are WIN for Windows, MAC for Macintosh, and POSIX for POSIX (Linux or UNIX). It is also used to allow for the possibility of more than one locale per country and language combination. Most European countries also now have the EURO variant for currency formatting.

Exec xp_sendmail @recipients = 'SQLAdmin; NetAdmin', @query = 'DBCC SQLPERF (LogSpace)', @subject = 'Transaction Log usage', @attach_results = 'TRUE'

Although no facts are stored in a factless fact table, it does support measurement of the business process. It can be used to answer a wide variety of analytic questions, simply by counting rows in the fact table. Dimensions can be used to filter or group the counts in a variety of useful ways. Using the contact_facts star, it is possible to measure how often a customer is contacted by counting rows in the fact tale. This is done by choosing an arbitrary column in the fact table to count. The number of times John Smith was contacted during the month of January 2009 can be measured by the following query:

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