Demo store. Yuktikara is a fictional company from a Microsoft Fabric series. Nothing here is for sale. About this demo · How it’s built
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How Yuktikara runs on data
Yuktikara is a fictional retailer, but its data platform is real Microsoft Fabric, built by hand one episode at a time in the series Yuktikara Store: Microsoft Fabric, End to End. Here’s how a sale in a store, a click on this website and a tag on a shelf become answers an AI agent can give, and which parts exist yet.
Yuktikara / architecture explorer
From a shop floor to a smarter decision.
Six stages. One connected story. Follow a journey, explore an episode, or trace a component.
Capture
Shops & sensors
Prepare
Generate & refresh
Store
OneLake & real time
Connect
Business meaning
Understand
Reports & agents
Act
People & workflows
Selected component
Pick a component
Select any box on the map to see what it does, where its data comes from and where it goes next. Or follow one of the journeys above.
Receives from
Select a component to see its inputs.
Passes to
Select a component to see its outputs.
One question, four answers
“What were our sales?” sounds simple. The data holds at least four believable answers, and only one of them is right. The gap between the first and the last is 20.3%. The definition belongs in one place, a measure in the semantic model, and the ontology holds the pieces it works on: order status, line amounts, and accepted returns with the day they were accepted.
- Gross, every order$13.88M
Counts cancelled and pending orders, and ignores markdowns and returns
- Order total$13.02M
Only real sales, but includes sales tax
- Subtotal$12.03M
Right orders, no tax, but forgets the returns
- ✓ Net sales$11.06M
Completed and Shipped orders, minus accepted returns on the day they're accepted. No tax
Sales is only the most familiar example. The same data covers buying, stock month by month, promotions and each store’s plan, so it also answers which supplier is letting us down, which shelves need refilling, whether the clearance paid, and which stores are behind plan. A platform built for one question answers one question.
Published snapshot, Jan 2025 to Aug 2026. The refresh notebook regenerates the data up to yesterday, so its figures move, but the gap stays close to 20%.
Build log
- NowLive
This storefront
The website you’re on, built from the same synthetic dataset the series uses.
- Ep 1Building now
Foundation
Store data, the generator and load notebook, Lakehouse, ontology and graph
- Ep 2Planned
Two agents
The semantic model, then the lakehouse agent against the ontology agent, on six real scenarios
- Ep 3Planned
Live floor
RFID readings streamed through an eventstream into an eventhouse, and bound to the ontology
- Ep 4Planned
Watching agent
One rule on floor stock, and an operations agent that asks in Teams
- Ep 5Planned
Store app
An app where managers work through replenishment tasks
- Ep 6Planned
One assistant
Copilot Studio, the ontology over MCP, and the returns policy index