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 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. Operations knows which shipments count as flown. 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
- Food production & quality“Which inspection results actually count as passed?”Why one pass-rate question produced two confident answers — and how the quality team's agreed definition became the one AI uses.For quality and operations teams · Quality · Operations · FinanceSee the Food production & quality story
- Air cargo“How much of what we booked actually flew?”How a cargo team agreed what 'booked actually flew' means — cohort, cutoff and weight — so planning and AI work from the same number.For cargo operations and commercial teams · Cargo operations · Commercial planning · FinanceSee the Air cargo story
Start a free pilot
We work through one business question with you: agree its meaning, map it to the relevant data and review how it works on Snowflake or Databricks. We agree the scope together before we start.
- 01One business question
- 02One owner of the definition
- 03The data it depends on
- 04A review on your platform
- Start a free pilotWatch demo