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Business systems capture data from ongoing operations, whether the data is entered by a human being or generated by an automated process, and often store this data in a relational database. As a database administrator, you re already familiar with the virtues of a relational database for supporting business operations. You ve also likely encountered its limitations when people want to start using the relational database as a source for analysis. At its simplest, the preparation of data for analysis requires summarization of detailed transaction data. However, data preparation becomes more difficult when you need to support analysis of data over time, such as year-over-year growth, or to discover patterns, such as the characteristics of people who are likely to buy a particular product. SQL Server 2005 Analysis Services, also known as Analysis Services, enables you to easily implement an infrastructure that supports a wide range of analytical capabilities, from ad hoc queries to data mining. Because there are too many features to cover in-depth in a single chapter, we ll focus instead on the basic Analysis Services concepts required to build a functional database. We ll also review important administrative activities to manage a database after it is placed in production.

Analysis Services is the SQL Server 2005 component that provides two very different, but complementary, analytical capabilities: online analytical processing (OLAP) and data mining. An OLAP engine is popular for enabling fast ad hoc queries by end users. A user can interactively explore data by drilling, slicing and dicing, or pivoting. By drilling, a user can navigate from summarized data into successively more detailed data when

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The ThreadStart delegate performs a duty similar to that of the Runnable interface. Recall that the ThreadStart delegate is used to associate a method with an instance of the Thread class. That method can be static, belong to the current instance of the class, or belong to some other class. The run method of the instance of the class that supports the Runnable interface cannot be static. This means it must be an instance method. To state the obvious, that method must belong to the class that supports the Runnable interface. All this means is that the J# approach is slightly more restrictive than the delegate-based approach used by the framework. Since J# is a .NET language, there s no reason that the System.Threading.Thread class can t be used. Most likely the Runnable approach will be used when porting Java source code to the .NET environment.

querying an OLAP database to narrow the focus of analysis. A user slices and dices by placing data in a cross tab report with categories on both rows and columns to see the intersecting values. A user pivots by switching categories between rows and columns or by moving categories from the cross tab into a filter or out of the report altogether. A data mining engine, on the other hand, is more often used behind-the-scenes by technical specialists and subject matter experts to uncover hidden patterns in corporate data. These patterns can be used to develop profiles of people or events which can then be used to support decisions, such as which prospects to target in a marketing campaign or which products to promote together. Data mining can also be used for prediction, such as determining which customers are likely to stop using your products or services.

Analysis Services 2005 is the next generation of Analysis Services 2000, which itself was based on technology first introduced in SQL Server 7.0 as Microsoft OLAP Services. Data mining capabilities were added in Analysis Services 2000, hence the change in the component name in the SQL Server 2000 release. While conceptually the types of analysis supported by Analysis Services 2000 and Analysis Services 2005 are similar, the Analysis Services 2005 architecture is much different to support a broader array of analytical requirements than Analysis Services 2000.

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The new architecture of Analysis Services provides a rich set of features that support more complex design models, enhance manageability, and improve scalability. Whether your job is to build or to maintain an Analysis Services database, there are a number of enhancements that simplify your efforts. You can find a complete list of these new features in the SQL Server Books Online topic Analysis Services Enhancements. Let s briefly review the most important changes to understand as you get familiar with Analysis Services. Experienced Analysis Services developers and administrators immediately notice the separation of the development and administration environments. Developers now use an integrated development environment, SQL Server Business Intelligence Development Studio, in which they can switch easily between different types of database objects, debug complex calculations, and manage team development using a source control application such as Microsoft Visual SourceSafe. Integration with the .NET Framework enables developers to embed Analysis Services functionality into custom applications or to create stored procedures as better-performing replacements for userdefined functions. Administrators can access a variety of tools in a single management environment, SQL Server Management Studio, where they can configure and manage multiple servers, develop and execute XML for Analysis (XMLA) scripts to automate

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CONCURRENCY CONTROL IN J#

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