Will use the star schema shown figure

The cross tabulation in this example is a 2D (two dimensional) aggregation. But this is just a special case. For example, if other automobile models (such as Dodge, Ford, etc.) are added, it becomes a 3D aggregation. Generally speaking, the traditional GROUP BY clause in SQL can be used to generate the core of the N-dimensional data cube. The N-1 lower-dimensional aggregates appear as points, lines, plains, cubes or hyper-cubes in the original data cube. For this reason, a data CUBE operator was proposed [Gray, Bosworth, Layman and Pirahesh 1996].

© 2000 by CRC Press LLC

11.1 and Table 11.4 will be frequently cited by examples in the rest of this chapter.

11.3.3.5 Granularity and aggregation levels
In OLAP, data can be examined at different levels.

11.4.1 REVIEW OF A POPULAR DEFINITION
Earlier in Chapter 4, we provided a brief discussion on data warehouses based on a business perspective. However, this discussion requires some further technical clarification. For example, we said that a data warehouse consists of a copy of data acquired from the source data. What does this copy look like? In fact, we may need to distinguish between a "true" copy (duplicate), a derived copy, approximate duplicate, or something else. For this reason, we need to examine the concept of data warehouse in more depth. In fact, a data warehouse can be characterized using materialized viewsand indexing. In the following, we will examine these two issues.

© 2000 by CRC Press LLC