Give AI the business understanding your people already have.
Capture how your business works and put that meaning to work in Snowflake and Databricks.
From business meaning to platform execution
Defined by the business
Net revenue
= gross revenue − discounts − credits
- Owner
- Finance
- Used for
- Quarterly reporting
Duodata model
Your business meaning, ready for AI
One agreed definition with an owner, a time grain and the words people use to ask for it.
Choose your platform
Your platform executes the calculation. Pick one; you don't need both.
AI answer
Net revenue grew 5.4% from Q2 to Q3.
Definition used: net revenue = gross revenue − discounts − credits (owner: Finance).
Fictional example
AI can give you a confident answer to the wrong business question.
Ask how much revenue grew and an assistant will find a revenue column and answer fluently. Whether it used the revenue your finance team reports is another matter.
Question
“How much did revenue grow?”
AI answer without the business definition
Revenue grew 10%.
Gross revenue: $10.0m → $11.0m. The gross-revenue answer is 4.6 percentage points above the growth Finance reports.
Gross revenue, Q2 vs Q3 2026
Growth: 10.0%
| Component | Q2 | Q3 |
|---|---|---|
| Gross revenue | $10.0m | $11.0m |
| Discounts | $0.5m | $0.8m |
| Credits | $0.2m | $0.4m |
| Net revenue | $9.3m | $9.8m |
Fictional example in USD. Not customer data.
Your people know what the numbers mean.
Finance knows what counts as net revenue. Claims teams know which recoveries belong in a period. Duodata captures that meaning in plain language, with an owner. Your existing reports and models are the starting point.
How business ownership worksYour platform runs it natively.
Engineers map that meaning to real tables and deploy it as Unity Catalog metric views or Snowflake semantic views — in your account, your Git and your release process.
See the engineering viewStart where your role starts.
Executives
See the decision a number supports and who owns its meaning.
Open the executives viewBusiness analysts
Capture definitions, ownership and the semantic layer your teams rely on.
Open the business analysts viewBI and data analysts
Follow mappings, tools, lineage and validation behind each measure.
Open the bi and data analysts viewData engineers
Inspect schemas, mappings and native platform output.
Open the data engineers view
Built for Snowflake and Databricks.
Duodata puts business meaning to work in Databricks and Snowflake — where your data and AI assistants already run.
Native Apps and a delivered engineering workflow.
Databricks App
Deploy and maintain Unity Catalog metric views used by AI/BI Genie.
Explore Databricks AppSnowflake Native App
Deploy and maintain Snowflake semantic views used by Cortex Analyst.
Explore Snowflake Native AppDelivered data workflows
Transformations, facts, dimensions and reconciliation, built with your engineers.
Explore Delivered data workflowsWorked examples
- AI for finance and planningFinance & FP&AGive AI the meaning behind your financial numbers.“Sales grew 10%. How much did net revenue grow?”Explore the Finance & FP&A example
- Business meaning for insurance analyticsInsuranceGive every claims question a clear business definition.“Premium collections grew. Why did our net claims payment ratio rise?”Explore the Insurance example
Bring your use case
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