Methodology
How Data + AI becomes a decision
A clear, end-to-end view of the lakehouse architecture behind every recommendation.
Data foundation
Databricks stores all sales, inventory, products, and store data. Raw feeds land in Bronze, get cleaned in Silver, and roll up into Gold tables with consistent business definitions.
Risk logic
Stockout risk is derived from days of supply (current stock / avg daily sales). Waste risk is derived from perishability, days until expiry, and current stock. Recommended actions follow clear, auditable business rules.
Natural-language layer
The user asks in plain English. The assistant classifies the question into one of seven safe intents and only queries approved Databricks views — never raw SQL. Answers come back as summary, chart, table, and recommended action.
Why Databricks
Databricks powers the trusted backend. Gold tables make business logic reusable. Views make dashboards and AI answers consistent. The same lakehouse supports dashboards, storytelling, and natural-language experiences.
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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