| A collection of related data
members. The members can be organized in a hierarchical structure (for example
in a Geography dimension) or a flat structure (for example in a Measures
dimension). Dimensions can be nested so that a crosstab or chart can display
more information, making it easier to compare.
Nesting dimensions means placing two
or more dimensions on the same axis. For example, you may want to view data for
different sizes of stores, in different cities, against the products the stores
sell. You could nest the Stores and Cities dimensions on one axis. For more
information, see the
BusinessObjects Voyager
User's Guide.
|
| Online
Analytical Processing (OLAP) applications are designed from the start with
online data analysis in mind. To reduce processing time to the minimum,
database data is summarized and pre-consolidated into matrix table format.
Because these tables usually have three (or more) dimensions, they are referred
to as data
“cubes”. If a relational database
can read about 200 records per second and write 20, a good OLAP server, using
row and column arithmetic, can consolidate 20,000 to 30,000 cells (equivalent
to relational records) a second. This, the much smaller storage space OLAP data
requires, and faster access due to more efficient indexing, are the keys to
OLAP reporting speed, which is two or three orders of magnitude faster than
relational technology
|
| Any of the three spatial axes on a
Voyager
crosstab or chart component. For example, a
Voyager
crosstab appears as a two-dimensional table, similar to an Excel spreadsheet.
The crosstab has two
“view” axes, similar to Excel's
vertical and horizontal axes. The two view axes are called the row axis and
column axis. In addition, by visualizing the two-dimensional object as being a
“slice” of a three-dimensional
object, and allowing the position of the slice to change, you can think of a
third axis as being perpendicular to the screen. This is the slice axis.
Therefore, a
Voyager
crosstab axis is any one of those three spatial axes.
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