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TIP A time-stamped dimension adds non-overlapping effective and expiration dates for each row, allowing each type 2 change to be localized to a particular point in time. The effective date can be used to order a transaction history; the effective and expiration dates allow filtering for a specific point in time; a most_recent_version column can simplify filtering for current status. This technique can be elaborated upon for situations where multiple discrete changes must be captured during a single day. While it represents additional work to maintain a time-stamped dimension, it pays dividends when it comes to maintaining associated fact tables. NoTE It might be more precise to refer to this example as a date-stamped dimension, since time of day is not being recorded. As you will see, this technique can be expanded to capture time of day. The term time stamp is a popular shorthand for describing any temporal designation, regardless of specificity. Some designers prefer to refer to this technique as effective dating. Kimball and Ross refer to dimension tables that track effective and expiration dates as transaction tracking dimensions.

Table 5-10.

Despite the difficulties it presents in an ad hoc query environment, the snapshot fact table design can be a powerful tool. It may be useful to provide both transaction and snapshot representations of the same process; like two sides of the same coin, these models provide different and valuable perspectives of the same activities. The snapshot need not be limited to containing facts for balances or levels; these may be supplemented with other facts, most of which will be fully additive. Careful attention must be paid to the impact of slowly changing dimensions when it comes to snapshots. Schema designers and ETL developers must be cognizant of these impacts.

SELECT OFFICE FROM OFFICES WHERE (SELECT SUM(QUOTA) FROM SALESREPS WHERE REP_OFFICE = OFFICE) > TARGET) But this isn't a legal SQL1statement Instead, you must turn the inequality around: SELECT OFFICE FROM OFFICES WHERE TARGET > (SELECT SUM(QUOTA) FROM SALESREPS WHERE REP_OFFICE = OFFICE) In this simple example, it isn't hard to "turn the logic around," but the restriction is a nuisance at best, and it does prevent you from comparing the results of two subqueries, for example Limited row-expressions Suppose you wanted to list the suppliers, item numbers, and prices for a set of products that are substitutes for one another.

Transaction versus snapshot is not an either/or decision The snapshot and transaction models reflect two aspects of the same process The transaction model allows detailed analysis of the process activities, placing them in a rich dimensional context The snapshot model sacrifices some detail, but allows flexible and powerful analysis of the effect of the transactions Each provides a different but important form of analysis, and many implementations will include both In the case of the banking example, the transaction model from Figure 11-1 allows a close study of banking activities Transactions can be studied by type, branch, teller, primary account holder, and so forth Each of these dimensions includes a wide variety of attributes that can be used to further shed light on the activities that make up the account management process.

In addition to the tools available within Enterprise Manager, you can monitor performance using other Windows NT/2000 tools. For more information on using Performance Monitor, see 3, Data Protection in Windows NT/2000. In this section, we ll look at some specific parameters that are related to replication performance. When SQL Server is installed, you ll be able to access various Performance Monitor counters related to replication. The easiest way to access a Performance Monitor chart with useful information is to right-click the Replication Monitor item in Enterprise Manager and select Performance Monitor. This automatically opens a chart with useful information pertaining to replication (see Figure 8-21). Table 8-2 lists some of these objects and counters.

Conceptually, these are a set of products whose "identification" (a manufacturer-id/product-id pair) matches one of a set of values, and it would be natural to write the query using a setmembership test as: SELECT MFR_ID, PRODUCT_ID, PRICE FROM PRODUCTS WHERE (MFR_ID, PRODUCT_ID) IN (('ACI',41003),('BIC',41089), ) The SQL1 standard doesn't permit this kind of set-membership test Instead, you must construct the query as a long set of individual comparisons, connected by ANDs and ORs Limited table-expressions.