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On the desktop, click the Shortcut To Offline Files icon. This folder contains the files you selected in step 8. While you are connected to the network, you will make changes directly to the files on the network share. When you log off or shutdown, these files synchronize so that you can use them offline.

The most common usage for the CheckBox control is to allow the user to make a binary decision about an option by either checking the box or not checking it. Typi cally, the check box is used for non-exclusive options; that is, checking a particular check box usually does not affect the state of other text boxes. Figure 3-7 shows an example of a hypothetical pizza order form. Radio buttons are used to choose between the exclusive options Pizza or Calzone, and CheckBox controls are used to select toppings for the pizza or calzone that is selected.

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to use in standardizing the data The transformation requires a connection to an instance of SQL Server 2005 to create the temporary SQL Server tables that the transformation algorithm requires to do its work The connection must run under the account of a user who has permission to create tables in the database To configure the transformation, you must select the input columns to use when identifying duplicates, and you must select the type of match fuzzy or exact for each column An exact match guarantees that only rows that have identical values in that column will be grouped A fuzzy match groups rows that have approximately the same values The method for approximate matching of data is based on a user-specified similarity score The transformation output includes all input columns, one or more columns with standardized data, and a column that contains the similarity score.

This section covers the tools you need to gain control over serialization as is required in some situations. It discusses those situations and explains how you can declare the right serializer to use.

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The score is a decimal value between 0 and 1 The canonical row has a score of 1 Other rows in the fuzzy group have scores that indicate how well the row matches the canonical row The closer the score is to 1, the more closely the row matches the canonical row The transformation does not remove duplicate rows, but instead groups them by creating a key that relates the canonical row to similar rows The Fuzzy Grouping transformation includes two features for customizing the grouping it performs: token delimiters and similarity threshold The transformation provides a default set of delimiters used to tokenize the data, but you can add new delimiters that improve the tokenization of your data The similarity threshold indicates how strictly the transformation identifies duplicates You specify the similarity threshold among rows and columns by setting the MinSimilarity property at the component and column levels.

You will continue to fill in information on these maps and create other design docu ments as you work through the other lessons in this chapter.

SQL Server 2005 provides a flexible and granular way to restore damaged data. To recover an entire database, you can perform a full restore along with restoring differential and transaction logs. You can use the STOPAT option to restore a database to a particular LSN, named transaction, or point in time. You can restore individual filegroups, and as long as the primary filegroup is not restored, the rest of the database can remain online and operational. You can restore individual pages to fix corruption issues. Restore operations can continue past bad sectors within backup media to make a best effort to recover as much data as possible.