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What Is Analysis Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .659 Designing Analysis Services Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .668 Managing Analysis Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .689 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .709
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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.
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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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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.
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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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