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Multi-Dimensionality In VisiCube

Multi-Dimensionality
Multi-dimensional data modeling is popular today and for good reason. It is a very powerful and flexible way to model actual phenomena in the real world. Any measurement (of a phenomenon) can be classified (or identified) through myriad attributes (who, what, where, when, how, etc). Each of these attributes are used as individual dimensions in this model. And the number of such attributes is unlimited.

Hypercubes
The term hypercube is utilized to communicate the nature of this model. A hypercube is a cube-like logical model in which all measurements are organized into a multidimensional space.

Record
#
Year
dimension
Sex
dimension
State
dimension
Height
measure
Weight
measure
12004MaleIdaho74182
22004FemaleOhio62128
32003MaleOhio70174
42004FemaleIdaho65159
52004MaleIdaho71147
62003MaleIdaho74203

The "Cube" in VisiCube
In building your data universe (the VisiCube project in which you will explore that data), your measurements are captured in a hypercube which supports analysis through any number of independent dimensions of that data.

However, VisiCube does this with a minimum of imposition, doing its best to buffer you from the complexities of that model. Specifically, the hypercube data model is built for you automatically (though you can override its structure) upon creation of a project and presented to you in a straight-forward, intuitive manner thereafter.

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