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One of the main problems with restoring data in the event of a full system crash is the number of steps that might be required before performing a restore operation. Typically, this includes the following process: 1. Replace failed hardware (if any). 2. Reload the operating system along with any necessary updates or patches. 3. Reinstall all required drivers, including those for the backup device. 4. Install the backup software. 5. Begin the restore process. In 7, Recovering the Data, we'll look at these operations in more detail. The overall process need not involve this many time-consuming steps, however. Many backup packages offer disaster recovery options that can be used to boot the system from a minimal set of diskettes (or other media). These boot disks load a minimal operating system that accesses your tape device and directly restores your information. The result is the savings of a great deal of time by avoiding the process of reinstalling the OS and all necessary drivers and software. Apart from the convenience, the investment in disaster recovery options can be priceless when you need to replace a failed mission-critical server, for example, where downtime is very costly. If a disaster recovery option is available with your selected backup software package, you should consider purchasing that option.

When a dimension attribute may take on more than one value for any given row in the table, we face a similar design challenge. How does one model an indefinite number of attribute values for a single row in the dimension This situation is common. Customers have multiple phone numbers. Bank accounts have multiple account holders.

An import operation An export operation A query that is used for export information A format file A file that is used for import/export operations max_errors Operation will abort if more than this number of errors occurs. Uses a format file created with the format option; prompts for additional information if not provided in the command. Specifies the path of the error file to which rows that could not be transferred are stored. Requires use of the -f switch.

There is no ambiguity about the order in which the tables are joined, or about which joins are inner or outer joins Overall, the added capability is well worth the added complexity introduced by the extended SQL2 FROM clause Although none of the query examples included in this section had WHERE or ORDER BY clauses, they can be freely used with the extended FROM clause in SQL2 The relationship among the clauses is simple and remains as described earlier in this chapter The processing specified in the FROM clauses occurs first, including any joins or unions The join criteria specified in a USING or ON clause are applied as a part of the particular join specification where they appear When processing of the FROM class is complete, the resulting table is used to apply the selection criteria in the WHERE clause.

Students have multiple guardians. Patients have multiple medical conditions. In each case, a small subset of the dimension s attributes may take on more than one value for a single natural key value. Attributes that may take on multiple values for a single dimension member are called multi-valued attributes. For example, in a dimension that captures business customers, it may be necessary to capture the company s industry. Each company has a single name, headquarters location, and chief executive. Most companies are in a single industry, as well, but some are in two, three, or any number of industries. Figure 9-8 illustrates this challenge. Company C operates in two industries, and it is possible that other companies may have three, four, or any number. Like the multi-valued dimension, this challenge can be resolved by simplifying the problem or by using a bridge table. Simplifying a multi-valued attribute is often the best approach but sometimes limits analytic possibilities. Implementing a bridge provides increased analytic flexibility but introduces risk. If used, the bridge will be placed between the dimension and an outrigger. As in the multi-valued dimension scenario, bridging a multi-valued attribute will introduce the risk of double-counting. Any given fact may link to more than one value for the bridged attribute, giving rise to the same set of problems encountered earlier. While the entire dimension table is not at risk this time, the repeating attributes are.

Table 6-6.

Industry Manufacturing Services Manufacturing Services Finance Some customers have more than one industry.

Thus, the ON clause specifies search criteria that apply to specific joins; the WHERE clause specifies search criteria that apply to the entire table resulting from these joins..

Notes Indicates the number of the first row to be copied. Indicates the number of the last row to be copied. Specifies the number of rows per batch copy operation. (A higher number will usually result in better performance.) Uses native data types for field values. (Without -n, the user is prompted.) Uses the char data type for copying. Uses Unicode characters (nchar) data type for copying. Uses native data types for noncharacter fields and Unicode for characters. Uses the SQL Server 6.x data types. (Does not prompt for information.) Specifies that quoted identifiers should be used (for example: data value ). Can use ACP, OEM, RAW, or a number for the code page. Used between values. (Default is \t.) Used between rows. (Default is \n.) Specifies the name of a response file that will answer the prompts.