Build and maintain the layers behind your AI.
Use your business definitions, source mappings and engineering standards to generate warehouse transformations, build facts and dimensions, and validate the results from source to output. Keep the work in your Git repository and execute it through your data platform and deployment workflow.
Replace repetitive modeling and transformation work with a repeatable engineering workflow. Bring the gold or silver workflow you want to simplify.
From business definition to reconciled output
Net revenue, end to end: definition, mapping, silver input, gold view, native semantics and the source-to-gold check.
On this selection, demo is a Unity Catalog catalog: demo.gold.revenue_by_quarter.
Net revenue = gross revenue − discounts − credits
Owner: Finance. Calendar quarters, USD, non-null decimal amounts.
Fictional example. The website computes these rows locally; it does not run SQL in a warehouse.
One engineering story within your platform
A coding harness and skills may generate transformation work; your warehouse and deployment tooling execute it. The Native App focuses on semantics, not on running every ingestion or transformation step.
- 01
Bronze
Source inputs and source totals used for reconciliation.
- 02
Silver
Existing structures and transformations, including mappings into a data vault where applicable.
- 03
Gold
Generated and maintained facts, dimensions and information-mart artifacts.
- 04
Semantics
Native semantic views and metric views exposing business meaning to analytics and AI.
Bring the gold or silver workflow you want to simplify.
We start with one business question, the person who owns its meaning, the data behind it and the result you expect. A scoped, paid proof of concept puts that meaning to work in your platform.
- 01One business question
- 02One owner of the definition
- 03The data it depends on
- 04The result you expect
- Bring your use case