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Quickstart: 10 common functions

Overview

This page highlights the functions you’ll use most often when bringing in data, shaping dimensionality, filtering slices, and building time logic.

Use it as a shortcut to common formula patterns before moving to the full Function catalog.


10 common functions

Connect & adjust values

DATA

Use to bring uploaded or source data into a node.
Shape impact: returns the shape of the referenced data table.
Example: DATA("ERP", "Actuals", "Sales")

ADDEACH

Use to adjust each value individually without aggregation.
Shape impact: keeps the input shape.
Example: ADDEACH('Sales', 1)


Time logic & forecasting

ROLLFORWARD_ADVANCED

Use to project values forward with additional forecasting options.
Shape impact: keeps dimensionality and extends the time range into the projection horizon.
Example: ROLLFORWARD_ADVANCED('Sales', 'MarketGrowth')

RUNNINGSUM

Use to calculate cumulative totals over time.
Shape impact: keeps the input shape.
Example: RUNNINGSUM('Sales')


Filter & apply business rules

FILTER

Use to return a subset of a node, for example specific regions or products.
Shape impact: reduces the result set to matching rows.
Example: FILTER('Sales', "Region", ["EMEA", "APAC"])

IF

Use to apply business rules such as thresholds, caps, floors, or branching logic.
Shape impact: output follows the condition’s shape.
Example: IF('Margin' < 0, 0, 'Margin')


Shape dimensionality

EXPAND

Use to add dimensional detail with one or more levels.
Shape impact: expands to the full cross product of the specified levels.
Examples:
EXPAND('Sales', "Product")
EXPAND(0, "Year", "Region", "Product")

EXPANDSINGLE

Use to expand to specific level values only.
Shape impact: expands only to the specified values.
Example: EXPANDSINGLE('Sales', "Region", ["EMEA", "APAC"])

DROPLEVEL

Use to remove dimensional detail.
Shape impact: reduces the result by removing one or more levels and finer levels in the same dimension.
Example: DROPLEVEL('Sales', "Product")

ROLLUP

Use to aggregate to a higher level, for example Product → Category or Month → Year.
Shape impact: reduces the result to the specified levels.
Example: ROLLUP('Sales', "Year")


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