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Industry · Food production & quality

“Which inspection results actually count as passed?”

The pass rate depends on which inspection records belong in the denominator. Duodata connects the agreed definition to the inspection tables and deploys it as native semantics in Databricks or Snowflake, so AI answers with the rule your quality team owns.

For quality and operations teams · Quality · Operations · Finance

3:29 · English captions
Duodata overview — food production & quality. Illustrative demonstration with fictional data.
Worked example

Inspection pass rate, two definitions

The agreed definition becomes an explicit mapping: which table holds inspections, which values count as passed, and how conditionals are treated. That mapping deploys as a Unity Catalog metric view or a Snowflake semantic view — in your account, your Git and your release process.

Business termSourceNote
Inspectionqms.inspectionsOne row per closed inspection in the reporting window.
Passedqms.inspections.result = 'PASS'Final result after any conditional period resolves.
Conditionalqms.inspections.result = 'CONDITIONAL'Included or excluded per the agreed definition.
Reporting windowqms.inspections.closed_dateCalendar quarter, owned by Quality.
  • Observed schema of the quality tables, kept distinct from the business definition
  • Business-term mapping: passed, conditional, reporting window → physical columns
  • Native output: metric view (Databricks) or semantic view (Snowflake)
  • Definition changes reviewed once, then carried through with lineage

Illustrative mapping with fictional tables. Website examples do not execute in your warehouse.

Platforms

Put this meaning to work in your platform.

Databricks

The agreed definition deploys as Unity Catalog metric views, answered by AI/BI Genie.

Snowflake

The agreed definition deploys as Semantic Views, answered by Cortex Analyst.

Free pilot

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.