Multidimensional Space - Microsoft SQL Server 2008 Analysis Services - page 13

CHAPTER 2

IN THIS CHAPTER

. Describing Multidimensional

Space

Multidimensional Space

. Dimension Attributes

. Cells

. Measures

. Aggregation Functions

W orking with relational databases, we're used to a two-
dimensional space—the table, with its records (rows) and
fields (columns). We use the term cube to describe a multidi-
mensional space, but it's not a cube in the geometrical
sense of the word. A geometrical cube has only three
dimensions. A multidimensional data space can have any
number of dimensions; and those dimensions don't have to
be the same (or even similar) size.

. Subcubes

One of the most important differences between geometric
space and data space is that a geometric line is made up of
an infinite number of contiguous points along it, but our
multidimensional space is discrete and contains a discrete
number of values on each dimension.

Describing Multidimensional Space

We're going to define the terms that we use to describe
multidimensional space. To a certain extent, they are mean-
ingful only in relation to each other:

. A dimension describes some aspect of the data that the

company wants to analyze. For example, your
company would have a data with time element in it—
the Time could become a dimension in your model.

. A member corresponds to one point on a dimension.

For example, in the Time dimension, Monday would
be a dimension member.

. A value is a unique characteristic of a member. For

example, in the Time dimension, 5/12/2008 might be
the value of the member with the caption “Monday.”