About cubes
A cube is a multidimensional data structure, optimized for analysis. A cube supports applications performing complex analyses without performing additional queries on the underlying data source. A cube organizes data into the following categories:
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A measure is an aggregate, or summary, value, such as sales revenue or units of products.
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A dimension is a group, such as customers, product lines, or time periods, which aggregates measures. For example, a sales revenue cube contains data that enables viewing sales volume and revenues, both of which are measures, by customers, product lines, and time periods, all of which are dimensions.
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An attribute is a value that a cross tab developer can associate with a dimension. For example, a cross tab developer can specify that a quantity-in-stock value is an attribute that associates with the product line dimension.
Dimensions can contain multilevel hierarchies. For example, a region dimension can contain a hierarchy of the following dimensions: country, state, and city. A time dimension can contain a hierarchy of the following dimensions: year, quarter, month, and day. Most cubes include time dimensions, because displaying measures by day, week, month, quarter, or year, is important for data analysis. In a cube, the time dimension is a special dimension, which supports storing data in the time periods a cube developer chooses.
A developer uses Actuate BIRT Designer Professional to create a cube that contains data from one or more data sources. Then, the developer creates a cross tab that uses the cube data and specifies the cross tab appearance. The initial cross tab that appears in Data Analyzer typically displays a portion of the available cube data in a simple, easy-to-understand layout. Figure 1-3 shows a cross tab and all the cube measures and dimensions that are available for analysis.
Figure 1-3  

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