What is an Analytic Workspace Model?

Within an analytic workspace, a model is a set of interrelated equations that can assign results either to a variable or to a dimension value. For example, in a financial model, you can assign values to specific line items, such as gross.margin or net.income.

gross.margin = revenue - cogs

When an assignment statement assigns data to a dimension value or refers to a dimension value in its calculations, then it is called a dimension-based equation. A dimension-based equation does not refer to the dimension itself, but only to the values of the dimension. Therefore, when the model contains any dimension-based equations, then you must specify the name of each of these dimensions in a DIMENSION statement at the beginning of the model.

When a model contains any dimension-based equations, then you must supply the name of a solution variable when you run the model. The solution variable is both a source of data and the assignment target of model equations. It holds the input data used in dimension-based equations, and the calculated results are stored in designated values of the solution variable. For example, when you run a financial model based on the line dimension, you might specify actual as the solution variable.

Dimension-based equations provide flexibility in financial modeling. Since you do not need to specify the modeling variable until you solve a model, you can run the same model with the actual variable, the budget variable, or any other variable that is dimensioned by line.

Models can be quite complex. You can:

• Include one model within another model as discussed in "Nesting Models"

• Use data from different time periods as discussed in "Using Data from Past and Future Time Periods"

• Solve simultaneous equations as discussed in "Solving Simultaneous Equations"

• Create models for different scenarios as described in "Modeling for Multiple Scenarios"