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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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routine tasks, and configure properties for database objects Importantly, the security model has been improved in Analysis Services so you can limit the administrative tasks that can be performed by specific users to certain databases or even selected database objects Developers of Analysis Services databases now have several new considerations for designing a dimension, a key component of an Analysis Services database Dimensions add context to numerical data under analysis by providing labels to describe the time, place, or people involved in a transaction or event Analysis Services 2000 imposed certain restrictions on the size, structure, and content of dimensions that have been eliminated in Analysis Services 2005 For example, now that dimension data is no longer stored in memory, you can work with very large dimensions without impacting server memory and without developing workarounds for the limit of 64,000 children per parent.

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Another significant difference in the structure of dimensions is the shift from a hierarchydriven design to an attribute-driven design If you used member properties in Analysis Services 2000, for example, you ll now use attributes to present this data More importantly, however, this new approach enables queries to support summarizations of values by arbitrary groupings, easily done in SQL queries against relational data but problematic when querying traditional OLAP structures As a result, Analysis Services now blurs the line between relational and multidimensional reporting You also have new options for managing data integrity While ETL processes should prevent data integrity issues in your source data, you can now gracefully accommodate orphaned records in the fact table for which a dimension reference does not yet exist by using a placeholder member.

The Fields window is populated with a list of the fields from the dataset that you use to build a report by placing these fields in freestanding textboxes or data regions. You can also use the XML data processing extension to build reports by using other tools that can access the Reporting Services API, as you ll learn in the next section.

By taking advantage of this feature, you can ensure the values in the OLAP database always match the values in the source system If, on the other hand, this behavior is not desirable, you can either force an error or ignore the error If you force an error, you can fix the problem before the database is available for querying While ignoring the error is a valid option, it s not recommended unless you re working on a prototype and are focused on getting the correct design before resolving data integrity issues Dimensions are still organized into a multidimensional structure called a cube, but there are some important conceptual differences between Analysis Services 2000 and Analysis Services 2005 In Analysis Services 2000, a single database can contain multiple cubes Each cube corresponds to one, and only one, fact table in a relational data mart or warehouse.

You can combine multiple cubes by creating a virtual cube when you need to analyze data across one or more fact tables A common use for a virtual cube is to compare.

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