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This form of the query joins the SALESREPS table to the OFFICES table to find the region where each salesperson works, and then eliminates those that do not work in the Western region. Either of the two queries will find the correct salespeople, and neither one is "right" or "wrong." Many people will find the first form (with the subquery) more natural, because the English request doesn't ask for any information about offices, and because it seems a little strange to join the SALESREPS and OFFICES tables to answer the request. Of course if the request is changed to ask for some information from the OFFICES table: List the names and ages of the salespeople who work in offices in the Western region and the cities where they work. the subquery form will no longer work, and the two-table query must be used. Conversely, many queries with subqueries cannot be translated into an equivalent join. Here is a simple example: List the names and ages of salespeople who have above average quotas. SELECT NAME, AGE FROM SALESREPS

NOTE: You can set up multiple publications for the same database. This is a useful scheme if, for example, you want to make different subsets of data available or if you want to use different replication methods for various Subscribers.

In other cases, keeping transaction details online may be possible but not feasible. The sheer volume of transaction details may be deemed too large to warrant maintaining more than a few month s worth online. These two scenarios would require establishing a pseudotransaction that represents the account balance as of the point in time at which the data warehouse begins tracking transactions. Computing balance from transactions is impossible if transactions are not stored at all. Sometimes, the volume of transactions is so great that transactions are purged daily and may not be stored in the data warehouse at all. How then to compute the status Last, there are some status-oriented measurements that do not correspond to transactions at all. Budgets, temperature readings, and reservoir levels are all examples of measurements that do not correspond to transactions.

Designers faced with the challenge of tracking both transactions and their effects may be tempted to store the status measurement as an additional fact in the transaction fact table You may be familiar with this approach if you have kept a handwritten log for your checkbook: each time you enter a transaction, you write down its amount and the new balance This approach might make sense in an operational system, where the focus is always the individual transaction, but it does not work well in analytic environments There are two reasons why it does not make sense to record a status, level, or balance with each transaction Perhaps the most obvious reason is that the transaction fact table is sparse If there is no activity on a particular day, there is no row in which to record this important fact.

Click the Properties & Subscriptions button in the Create and Manage Publications window, and you can view all the options that are available for each publication (see Figure 8-17). In some cases, you might want to make minor changes to the publication without going through all the steps in the wizard again. You can also perform other useful tasks, such as generating SQL scripts for creating this publication or setting valid logon information for replication.

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In the case of the bank account shown in Figure 11-1, for example, there is no row for February 9, since there was no transaction on that day If someone needed to know the total deposits at the branch as of the end of that day, it would be necessary to go through accounts one by one Each would be checked for activity that day If not found, the day before would be checked, and so forth, until a balance was found This process would have to be repeated for each account A potential workaround would be to record a row each day for accounts with no activity The transaction amount would be zero, but the account balance would be recorded This ensures that a balance is present for each account for each day but will clutter up reports that are focused on transactions.

Figure 8-17.

WHERE QUOTA > (SELECT AVG(QUOTA) FROM SALESREPS) NAME -------------Bill Adams Sue Smith Larry Fitch AGE --37 48 62