Databases Reference
In-Depth Information
CHAPTER
6
IN THIS CHAPTER
.
Cube Dimensions
Cubes and
Multidimensional
Analysis
.
The Dimension Cube
.
Perspectives
T
he main object you use in multidimensional analysis is
the cube. As opposed to the geometric cube, our multidi-
mensional cube (hypercube) can have any number of
dimensions, and its dimensions aren't necessarily of equal
size. It's not really a cube as we understood “cube” from our
geometry classes, but we've borrowed the term for multidi-
mensional analysis.
A cube defines a multidimensional space, the data available
for analysis, the methods for calculating the data, and
restrictions to data access. To define all this, a cube has two
main collections: a collection of dimensions that defines
the dimensions in our multidimensional space, and a
collection of data values (measures) that reside along those
dimensions and that we'll analyze. In Chapter 12, “Cube-
Based MDX Calculations,” we discuss the way cubes define
the rules for calculating the values of the cube. In the chap-
ters of Part 8, “Security,” we examine the rules that govern
access to the data in the cube.
The cube is a major object and accordingly has all the para-
meters that characterize the major object:
Identifier
,
Name
,
Description
,
Language
,
Collation
,
Annotation
, and a
collection of
Translations
. The
Language
and
Collation
parameters of the cube define the language for all the
elements that don't have those properties specified.
In the following list, we define the most important parame-
ters of the conceptual model of the cube:
.
Visible
determines whether the cube is visible to the
user or whether users accesses the cube's data through
other objects.
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