> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cfo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Translate dimensional modeling into cfo.ai concepts

> Connect familiar business-intelligence ideas such as facts, dimensions, grain, and cube cells to a cfo.ai Model.

If you are familiar with business intelligence or dimensional modeling, cfo.ai uses many of the same ideas with finance-friendly language.

## Common translations

| Dimensional-modeling term | cfo.ai concept                                       |
| ------------------------- | ---------------------------------------------------- |
| Measure or fact           | Variable                                             |
| Dimension or attribute    | Dimension                                            |
| Dimension entry           | Dimension item                                       |
| Group by, slice, or dice  | Segment by and filtering                             |
| Grain                     | The Dimensions and Date granularity used for a value |
| Cube cell                 | A Variable value at a segment, date, and scenario    |

## Variables are the values being measured

Revenue, Expenses, Units Sold, Headcount, and Gross Margin are examples of Variables. They occupy the value being calculated or displayed.

## Dimensions identify business context

Department, Region, Product, Customer, Account, and Date identify where a Variable's value belongs.

For example:

> Revenue = 100,000 at Department = Sales, Region = West, Date = January 2026, Scenario = Plan

Revenue is the Variable. Department, Region, and Date identify the cell address. Plan provides Scenario context.

## Grain explains what one value represents

Revenue by month has a different grain from Revenue by day. Revenue by Department and month has a different grain from company-wide Revenue by month.

Formulas recalculate at the requested grain. A margin shown by Department is calculated for each department rather than taking a company-wide margin and dividing it afterward.

## You do not need a data-warehouse design

Users do not need to build a star schema or cube to work in cfo.ai. The useful mental model is simpler:

* Variables are calculated values
* Dimensions organize those values
* A segment identifies a slice of a Variable's data.
* A cell address identifies one complete result, including its period.