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MSAS Listings
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Total:
70 | Displaying: 51 - 60 | Pages: << 1 2 3 4 5 6 7 >> |
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Cubes are made up of a fact table and several dimensions. Optimizing cube processing therefore, involves optimizing dimensions also. Let us look at two scenarios. One in which the dimensions are not optimized and the cube is processed and another in which the dimensions are optimized and the cube is processed.
Updated: 05/07/2005
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As stated earlier, maps are created when a dimension is processed. However, existing maps of a dimension are destroyed when it is processed and new maps are created. Consequently all cubes accessing the dimension will find it inaccessible and the cube will be invalid. The dimension will become accessible only when the cube is reprocessed.
Updated: 05/07/2005
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The Analysis server is like a black box. Everything that happens in the server is recorded, but the end user sees a multidimensional cube created out of the data in the data warehouse and has very little taste of what really goes on behind the scenes. In this section we will be examining this black box to understand how the Analysis server processes Dimensions and cubes. We will also learn how to optimize cube processing and how to troubleshoot cube processing
Updated: 05/07/2005
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SQL Server 2000 Analysis services comes with certain features that optimize performance without the intervention of the Administrator. The Storage Engine is optimized by incorporating the following features;
Updated: 05/07/2005
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This tutorial explains the usage of the Usage Based Optimization Wizard, The Server Cache , Query Usage and Manipulating the query log. Using the Usage Based Optimization Wizard
Updated: 05/07/2005
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Pre-calculated summaries of data that improve query response time are called aggregations. OLAP technology organizes data into the multidimensional structures of cubes. The dimensions and their hierarchies define the queries that can be asked of the cubes.
Updated: 05/07/2005
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The Storage Design Wizard helps the user set the storage options and design the aggregations for a cube. While choosing from the three available storage modes the user has to keep certain factors in mind.
Updated: 05/07/2005
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Online Analytical Processing (OLAP) is essentially data presented as Cubes, dimensions, hierarchies and measures. Users can navigate a complex set of data intuitively using these objects. In this context, consistent response times for each view or slice of data become important. Therefore modes of storing and retrieving data became the key tenet of storage design.
Updated: 05/07/2005
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Each object in the properties pane of the Cube Editor has its own set of properties which can be used to modify the settings of the object. The properties of a cube defined in the properties pane are as tabulated below. In this section we shall use these properties to set the properties of our cubes
Updated: 05/07/2005
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The quantitative and numerical columns from a fact table of a cube are the measures of the cube. When the cube is processed the data in the measures get aggregated across the dimensions of the cube. These measures are of primary interest to the end user and are the central values that get analyzed in a cube
Updated: 05/07/2005
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MSAS Listings
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Total:
70 | Displaying: 51 - 60 | Pages: << 1 2 3 4 5 6 7 >> |
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