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The second and more flexible method for activating a SOAP extension is by means of a custom attribute used to flag the methods in the Web service for which the SOAP extension must be used. This technique lets you apply the extension to just a subset of all the existing methods and allows you to define arguments that are passed to the SOAP extension, on a method-by-method basis. In the following sections, I ll show you how to implement a SOAP extension that mon itors access to any Web service method marked with a special SoapCustomAuthentica tionAttribute. The constructor for this attribute takes an integer that defines the minimum subscription level required for a client to invoke the method that has been flagged with the attribute. (This is the SOAP extension version of the authentication and authorization method described in the section Custom Authentication, earlier in this chapter.) For example, a method in SampleService.asmx that can be called only by clients whose subscription level is 2 or higher would look like this:

Your screen looks like this:

When you work through the security subsystem as it is used with Active Directory, you ll find the three following key areas:

5. Click Apply. Now any reports or subscriptions that use this shared data source will be suspended. 6. Click the Execution Log Reports link, and then click the Product Profitability Filter report link. Your screen looks like this:

Select ProductKey, FullDateAlternateKey, SalesAmount, OrderQuantity from FactResellerSales, DimTime where DimTime.TimeKey = FactResellerSales.OrderDateKey

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The fact is that values in a data warehouse are not changing as dynamically as they would in a production database, so storing the values redundantly is less important than is retrieving the values as quickly as possible for a report Consequently, in many data warehouses, all the attributes for a dimension are stored in a single dimension table even if that means that categories and years are stored redundantly many times Storing redundant values in a single table is called denormalizing the data The concept is that dimension tables are relatively small (compared to the fact tables), and that performing a single join to find out the Year and the Category is much faster with only a couple of joins, so denormalizing is worth doing.

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We have seen before that Xbox and Windows PC systems can be configured to use displays of different sizes. Some screens are 800 pixels wide and 600 high, and others can be 1280 pixels wide and 768 high. One of the things a well-designed game must do is make sure that it will work correctly on any display. However, Windows Phone lets you turn this on its head, in that it is possible for a Windows Phone game to insist on a specific display resolution:

In addition to publishing the CA certificates and CRLs to the local machine store of subordinate CAs, you can publish CA certificates and CRLs for any offline CAs to Active Directory. By publishing the CA certificates to Active Directory, you ensure the automatic propagation of CA certificates and CRLs to all Windows 2000, Windows XP, and Windows Server 2003 forest members. The published CA certificates and CRLs are automatically downloaded to the Windows 2000, Windows XP, and Windows Server 2003 forest members through Group Policy application. The application of Group Policy triggers the autoenrollment mechanism, initiating the automatic download of any certificates or CRLs published in Active Directory to the forest members. Figure 6-3 shows where the CA certificates and CRLs are published when they are published into Active Directory.

You should adopt standards when naming your tables and columns. Making good use of uppercase and lowercase letters and using underscores to separate words will help make the table and columns easier to read and understand. Try to keep the names short

This selector has any name you choose to give it, except that the name must begin with a period and shouldn t be the name of an HTML tag. Here are some examples:

Storing all the attributes for each dimension in a single denormalized dimension table produces what is called a star schema, because you end up with a single fact table surrounded by a single table for each dimension, and the result looks a bit like a star Normalizing each of the dimension tables so that there are many joins for each dimension results in a snowflake schema, because the points of the star get broken up into little branches that look like a snowflake In reality, it isn t the database that is star or snowflake, because one dimension might be fully normalized (ie, a snowflake), while another dimension in the same data warehouse might be fully denormalized (ie, a star) In fact, even within a single dimension, some attributes might be normalized into a snowflake while others are denormalized into a star.

Server-based storage locations both in memory (automatic) or on disk (designed) that enhance query performance. A calculation created using MDX that is added as a new member to the Measures dimension in a cube.

see the full width. The Document window looks like this:

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