Architecture

How trusted grocery data becomes business action

Trusted grocery data in the lakehouse becomes business metrics, AI-assisted insights, and faster inventory actions.

Grocery Data Intelligence uses Databricks Lakehouse layers to transform raw grocery data into trusted Gold metrics, then uses an AI-ready semantic layer and action flow to help business users move from insight to action faster.

End-to-end flow

From raw store data to confirmed business action.

Step 1

Raw Grocery Data

Stores · Products · Sales · Inventory

Step 2

Databricks Lakehouse

Bronze · Silver · Gold layers

Step 3

Semantic Layer / UC Metric Views-ready

Days of supply, stockout risk, waste risk, priority, recommended actions

Step 4

Genie-style Ask Data experience

Natural language over trusted business data

Step 5

LLM / FM API reasoning layer

Interprets the question, generates business-friendly answers

Step 6

Action Center

Reorder · Promotion · Discount · Donation · Monitoring

Step 7

Lakebase-ready OLTP layer

Reorder plans, action status, decisions, feedback history

Step 8

Business outcomes

Fewer stockouts, less waste, better planning, faster action

Databricks-native concepts we use

What's live today and what's planned next — labeled honestly.

Current Next step

Databricks Free Edition

Current

Build and demo without enterprise setup cost.

Lakehouse Architecture

Current

Foundation that moves grocery data from raw to clean to business-ready.

Bronze Layer

Current

Raw stores, products, sales, and inventory data.

Silver Layer

Current

Cleans, standardizes, and joins raw data so it's reliable for analysis.

Gold Layer

Current

Business metrics: days of supply, stockout risk, waste risk, priority, recommended action.

Databricks SQL / SQL Warehouse

Current

Powers the app, dashboard, Ask Data + AI, and approved views.

Gold Views

Current

Surfaces trusted data to the app instead of raw tables.

Unity Catalog

Current

Catalog / schema / table / view governance for trusted data assets.

Semantic Layer (concept)

Current

Consistent business definitions across dashboard, Ask Data, and actions.

AI/BI Genie-style experience

Current

Plain-English questions answered from trusted data — live for some intents today, powered by a Databricks-hosted Foundation Model.

UC Metric Views

Native Databricks semantic layer for reusable metrics like days of supply and reorder priority.

Materialized / Serving Tables

Faster dashboard and AI queries as data grows.

Lakebase

Store action state — reorder plans, task status, user decisions, feedback history.

Databricks Apps

Host the app closer to Databricks data and security.

Lakebase-ready action state

In a production Databricks App, Lakebase can store action state such as reorder plans, task status, user decisions, and feedback history. This helps the app move from dashboard insights to operational action tracking.

Action ID	Action Type	Products Included	Created By	Created Time	Status	User Feedback
act_00427	Reorder Plan	12 products · Bakery, Dairy	store.manager@northside	2026-06-09 06:14	Awaiting confirmation	—
act_00428	Donation Plan	5 products · Produce	store.manager@central	2026-06-09 06:18	Confirmed	Useful — partnered with food bank

Illustrative — Lakebase-ready schema for action state.

Methodology

Risk math, approved views, and validation status →

About

DAIS 2026 entry, story, and how to build this →