Data map

The assignment of each column in an export to a role: region, team, person, account as nesting levels; product and date as dimensions; value as the measure; the rest dropped. Checked by the roll-up identity before anything is computed, and reused on every later export of the same shape.

DefinitionThe assignment of each column in an export to a role: region, team, person, account as nesting levels; product and date as dimensions; value as the measure; the rest dropped. Checked by the roll-up identity before anything is computed, and reused on every later export of the same shape.

Value first, then account, then upward

The column that sums to the control total is the value. The finest identifier every row has is the account.

Product is not a level

The same product appears under many accounts. Mapped as a level, the roll-up double-counts.

How it is used

Each column of an export is assigned a role once: the nesting levels, the dimensions, the measure, the date and the identifier. A person confirms it, it is saved against the export's layout, and the same map is applied to every later upload.

Example

A ledger export maps Region, Branch, Rep and Account as levels, Category as a dimension, Invoice Date as the date and Net Value as the measure. Next month's file has the same headers and loads without anyone touching it.

Where it goes wrong

A column renamed in the source system. The map no longer finds it, and the right response is to stop and ask, not to guess.

Articles that use this term

How-to guides

How to map a spreadsheet's columns to a roll-up: a guide to the data map

What a data map is and how to build one from any sales export: the six roles a column can play, region, team, person, account, product, value, plus date, how to tell which column is which when the headers do not say, the columns to drop, the roll-up check that proves the map is right before anything is computed, and the mistakes that produce a map that looks fine and rolls up wrong.

16 Sept 20263 min read How-to guides

The exports by industry: the four files each desk drops, and what is in them

Every measure on this site is computed from a handful of exports a company already has. This hub gives, for twelve industries, the three or four files, which system each comes from, the columns that matter in each, the identifier that joins them, and the control total to note before exporting, so that a team knows exactly what to drop before it drops anything.

16 Sept 20263 min read How-to guides

The sales roll-up hierarchy: region, team, person, account, and why product is not a level

The four-level tree that every sales measure is summed through, the difference between a level and a dimension, the identity that must hold at each level, and the mapping decisions that make one hierarchy serve finance, sales operations and the salesperson at once.

16 Sept 20263 min read How-to guides

What a validation report should tell you before you trust an upload

The six lines a validation report on an uploaded sales file should carry before any measure is computed: the period it detected, the row and value totals against what the source showed, the columns it mapped and the ones it dropped, the roll-up identity at every level, the identifiers it did not recognise from last time, and the exceptions it will exclude. What each line catches, what a pass looks like, and why a report that says only 'upload successful' has told you nothing.

16 Sept 20263 min read Alternatives and comparisons

Switching from Adaptive Planning: what to export, what carries over, and how to run both

A practical guide to moving a team's questions off Adaptive Planning: what to export, how the data maps, what carries over, and running both side by side.

24 Sept 20263 min read Alternatives and comparisons

Switching from Alteryx: what to export, what carries over, and how to run both

A practical guide to moving a team's questions off Alteryx: what to export, how the data maps, what carries over, and running both side by side.

24 Sept 20263 min read