Transformer Documentation

Transformer turns inconsistent source data — messy spreadsheets, exports, and documents — into governed, export-ready datasets. You define the shape of the data you want once as a schema, then let AI-assisted mapping transform raw uploads into that structure and push the result to BigQuery.

How it fits together

The product is organized around four building blocks:

Concept	What it is
Folder	A workspace that groups related schemas (e.g. a division, business unit, or data domain).
Schema	The target structure — the fields, types, and definitions your clean data should conform to.
Dataset	A single transformation run: raw files mapped into a schema and reviewed for approval.
Main schema table	The consolidated BigQuery table that approved datasets are merged into.

The five-step workflow

This guide walks through the full path from an empty workspace to clean data in BigQuery:

Create a Folder — set up a workspace.
Create a Schema — define your target structure (4 ways).
Create a Dataset — start a transformation from a schema.
Upload Excel Files — bring in your raw data.
Add to Main Schema — review, approve, and merge.

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