> ## 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.

# From dimensional modeling to properties

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           | Metric property                                      |
| Dimension or attribute    | Dimension property                                   |
| Dimension member          | Dimension item                                       |
| Group by, slice, or dice  | Segmentation and filtering                           |
| Grain                     | The dimensions and Date granularity used for a value |
| Cube cell                 | A metric value at a segment, date, and scenario      |

## Metrics are the values being measured

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

## Dimensions provide coordinates

Department, Region, Product, Customer, Account, and Date identify where a metric value belongs.

For example:

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

Revenue is the metric. Department, Region, and Date provide coordinates. 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:

* Properties describe what the model knows
* Metrics are calculated values
* Dimensions organize those values
* A segment identifies one position in that organization