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Issue multiple queries that create temporary tables, then issue an additional query that joins the temporary tables Issue a single SQL statement that performs a full outer join on subordinate queries from each star Products have a variety of different names for this capability, including multi-pass queries, cross-stitching, multi-SQL, and the like Some configuration is usually required so that the tool will invoke the mechanism automatically If the business intelligence tool is unable to drill across, it will not be possible to generate reports that compare two or more business processes As you learned in 4, these are often high-value reports; the inability to produce them would be a serious blow to the analytic environment As already mentioned, there is a solution, and it can be incorporated directly into the schema design without compromising any of the best practices you have learned in this book.

Data Protection in Windows NT/2000

executed atomically all of the statements must be completed for the database to be in a consistent state Here are some examples of typical transactions for the sample database, along with the SQL statement sequence that comprises each transaction: Add-an-order To accept a customer's order, the order entry program should (a) query the PRODUCTS table to ensure that the product is in stock, (b) insert the order into the ORDERS table, (c) update the PRODUCTS table, subtracting the quantity ordered from the quantity-on-hand of the product, (d) update the SALESREPS table, adding the order amount to the total sales of the salesperson who took the order, and (e) update the OFFICES table, adding the order amount to the total sales of the office where the salesperson works Cancel-an-order.

When faced with a tool that cannot drill across, add a merged fact table to the dimensional design, as depicted in the bottom of Figure 16-4 The merged fact table stores the precomputed results of drilling across This shifts the burden from the.

Figure 3-7.

Business View Order Date Date Month Year Order Info Quantity Ordered . . . ORDER_ DAY (day) PRODUCT_ ORDERED (product) quantity_ordered ORDER_ FACTS ORDER_ CUSTOMER (customer)

To cancel a customer's order, the program should (a) delete the order from the ORDERS table, (b) update the PRODUCTS table, adjusting the quantityon-hand total for the product, (c) update the SALESREPS table, subtracting the order amount from the salesperson's total sales, and (d) update the OFFICES table, subtracting the order amount from the office's total sales Reassign-a-customer When a customer is reassigned from one salesperson to another, the program should (a) update the CUSTOMERS table to reflect the change, (b) update the ORDERS table to show the new salesperson for all orders placed by the customer, (c) update the SALESREPS table, reducing the quota for the salesperson losing the customer, and (d) update the SALESREPS table, raising the quota for the salesperson gaining the customer.

of the same information, but if you re wondering about general configuration of a machine, Windows NT Diagnostics is a quick way to get what you need.

Business View Shipment Date Date Month Year Shipment Info Quantity Shipped . . . SHIPMENT_ DAY (day) PRODUCT_ SHIPPED (product) quantity_shipped SHIPMENT_ FACTS SHIP_TO_ CUSTOMER (customer) SHIPPER

In each of these cases a sequence of four or five actions, where each action consists of a separate SQL statement, is required to handle the single "logical" transaction The transaction concept is critical for programs that update a database because it ensures the integrity of the database A SQL-based DBMS makes this commitment about the statements in a transaction: The statements in a transaction will be executed as an atomic unit of work in the database Either all of the statements will be executed successfully, or none of the statements will be executed The DBMS is responsible for keeping this commitment even if the application program aborts or a hardware failure occurs in the middle of the transaction, as shown in Figure 12-1 In each case, the DBMS must make sure that when failure recovery is complete, the database never reflects a "partial transaction".