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Duodata
Duodata Databricks App

The agreed definitions, running inside Databricks.

The Databricks App is how the meaning your business owns reaches Databricks: it produces the Unity Catalog metric views that AI/BI Genie reads, and keeps them in step when a definition or a source schema changes — reviewed by your team before anything ships.

The Databricks App produces Unity Catalog metric views used by AI/BI Genie, inside your Databricks account.

Start a free pilotBusiness view of Databricks
Workflow

From your definition to your platform, in five reviewed steps.

Every step produces something your team can read and approve — nothing changes in your platform without a review.

  1. 01

    Observe

    Inspect physical tables, columns and relationships in your platform.

  2. 02

    Connect meaning

    Map business definitions to their physical implementation.

  3. 03

    Refine

    Resolve the platform details that make a semantic model usable.

  4. 04

    Deploy

    Produce the native semantic artifact for your selected platform.

  5. 05

    Maintain

    Review changes to definitions, schemas and their mappings together.

Already have Ossie models? Start with the Native App in your platform, then connect Duodata's business definitions when your team needs shared ownership and meaning.

Maintain

When a source column changes, you see what it touches.

A renamed column surfaces the one affected mapping. The business definition and the reported totals stay the same — only the connection is updated, after review.

Mapping and native output match the observed schema.

1 · Observed schema

demo.gold.revenue_by_quarter

Unity Catalog catalog demo, schema gold, table revenue_by_quarter

  • credits DECIMAL(18,2)
  • discounts DECIMAL(18,2)
  • gross_revenue DECIMAL(18,2)
  • quarter DATE

2 · Mapping

Logical fact to physical column
LogicalPhysical
gross_revenuegross_revenue
discountsdiscounts
creditscredits

Business definition unchanged: net revenue = gross revenue − discounts − credits.

3 · Totals

Q2 net revenue
$9.3m
Q3 net revenue
$9.8m

Mapping current

Databricks metric view · revenue_semantics.sqlsql
CREATE OR REPLACE VIEW demo.gold.revenue_semantics
WITH METRICS
LANGUAGE YAML
AS $$
version: "1.1"
comment: Fictional quarterly revenue example.
source: demo.gold.revenue_by_quarter
fields:
  - name: quarter
    expr: source.quarter
measures:
  - name: net_revenue
    expr: SUM(source.gross_revenue) - SUM(source.discounts) - SUM(source.credits)
$$;

Fictional example. Nothing here runs against a warehouse.

Free pilot

Start a free pilot

Bring one business question and the model you want to deploy in Databricks. We agree the scope of a free pilot together before we start.