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MSAS Listings
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Total:
70 | Displaying: 1 - 10 | Pages: 1 2 3 4 5 6 7 >> |
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A logical dimension created out of the columns of a physical dimension is a virtual dimension. The contents of a virtual dimension are member properties of the physical dimension or columns and tables of a physical dimension. For instance the Store name level of the Store dimension has a member property named Store Sqft. This member property identifies the area of the store in square feet. This member property can be used to create a virtual dimension and this can be added to any cube that contains the Store Dimension.
Updated: 06/01/2006
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Member properties are attributes associated with members. They contain some additional information about a member but cannot be used to create a level in the dimension by themselves. For example each member of the Month level has an associated Boolean number property called Bonus month.
Updated: 06/01/2006
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To enable proper aggregation of values along a dimension each member of the dimension needs its own aggregation rule. These rules are provided by custom roll up. Custom rollup operators provide a simple way of controlling the process of rolling up a member to its parents values. Custom rollup operators assigned to a column during the process of creating a dimension. The rollup then, uses the contents of the column as custom rollup operator for each member and is used to evaluate the value of the member’s parents.
Updated: 06/01/2006
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Time dimensions are part and parcel of OLAP cubes. At the lowest level of detail a time dimension may contain a month, minute or even a second. At the most summarized level it may contain a year, a decade or a century. The repetitive nature of time encourages users to view data in terms of a time dimension. How much sales of x product occurred during the month of March or April in the year 2000 compared to the year 2001? This would be a query on a sales cube with a time dimension.
Updated: 05/30/2006
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A hierarchy defines the relative positions of members in a dimension. Hierarchies are sometimes represented as pyramidal structures. The members in this structure are arranged in an expansive order—from the most summarized to the most detailed. For instance in a geography dimension the country may the most summarized and the individual cities and localities may be the most detailed members of the hierarchy.
Updated: 05/30/2006
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Dimensions are stored in the Multidimensional OLAP or Relational OLAP. The storage mode determines the location and form of the dimensions data. While MOLAP stores data in a multidimensional structure on the Analysis server, ROLAP stores the data in the relational tables. The storage mode can be set using the Dimension or cube editor.
Updated: 05/30/2006
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Dimensions are defined as structural attributes of a cube made up of levels arranged in hierarchies. A level is a set of members of a dimension organized such that all members of the set are at an equal distance from the root of the hierarchy. A hierarchy is the set of members in a dimension and their positions relative to one another.
Updated: 05/30/2006
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Parent child dimensions when viewed from within a cube reveal some interesting features. We will add an private employee parent child dimension to the sales cube and study the features thereof.
Updated: 05/30/2006
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A level is an element of a dimension hierarchy that describes the hierarchy from the highest level to the lowest level of data. Levels exist within dimensions and are based on columns in the dimension table or member properties in the dimension. They specify the contents and structure of the dimension’s hierarchy and determine the members that are included in the hierarchy and their positions relative to one another within the hierarchy.
Updated: 05/30/2006
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Dimensions are created, based on dimension table columns, member properties, or from the structure of OLAP data mining models. When a dimension is defined, there are a number of possible approaches. Each approach produces a different dimension variety. Standard Dimensions are regular dimensions. They can be of two types. The standard star schema dimension and the standard snowflake dimension.
Updated: 05/30/2006
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MSAS Listings
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Total:
70 | Displaying: 1 - 10 | Pages: 1 2 3 4 5 6 7 >> |
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