Methodology
How Data + AI becomes a decision
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.
The Databricks stack we use
Databricks Free Edition
CurrentBuild and demo without enterprise setup cost.
Lakehouse Architecture
CurrentFoundation that moves grocery data from raw to clean to business-ready.
Bronze Layer
CurrentRaw stores, products, sales, and inventory data.
Silver Layer
CurrentCleans, standardizes, and joins raw data so it's reliable for analysis.
Gold Layer
CurrentBusiness metrics: days of supply, stockout risk, waste risk, priority, recommended action.
Databricks SQL / SQL Warehouse
CurrentPowers the app, dashboard, Ask Data + AI, and approved views.
Gold Views
CurrentSurfaces trusted data to the app instead of raw tables.
Unity Catalog
CurrentCatalog / schema / table / view governance for trusted data assets.
Semantic Layer (concept)
CurrentConsistent business definitions across dashboard, Ask Data, and actions.
AI/BI Genie-style experience
CurrentPlain-English questions answered from trusted data — live for some intents today, powered by a Databricks-hosted Foundation Model.
UC Metric Views
NextNative Databricks semantic layer for reusable metrics like days of supply and reorder priority.
Materialized / Serving Tables
NextFaster dashboard and AI queries as data grows.
Lakebase
NextStore action state — reorder plans, task status, user decisions, feedback history.
Databricks Apps
NextHost the app closer to Databricks data and security.
Approved Databricks objects
Schema: … · Every object below is queried by the app in production.
Business views
Gold tables
Validation status
Reported live from this running deployment.
Databricks connection
Checking…
Approved objects
0
Schema
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