The idea
Most businesses that sell limited capacity or run shifts ask the same questions every week: what to charge, how busy we’ll be, how many people to schedule, whether yesterday balanced and how this week compares with last year. The data to answer them is already in their systems. It’s rarely in a shape a manager can use before the morning meeting.
This toolkit is my answer, built in layers so it can move between sectors:
- A warehouse model. A star schema with facts for sales or bookings, stays or visits, and labour, and shared dimensions for date, site, product and channel.
- Data quality first. Ten automated checks (duplicates, impossible dates, negative prices, orphan keys, capacity breaches and more) run before any number reaches a dashboard.
- Decision tools. Pricing, demand forecasting, no-show planning, shift scheduling, daily close, KPI dashboards and more.
Editions
The hospitality edition came first, because I worked on a hotel floor in Niagara Falls and saw the problems up close. It runs on a five-hotel sample group with about 640,000 bookings.
The restaurant-chain and retail editions reuse the same model and checks. Bookings become orders or transactions, rooms become seats or stock, and each tool gets the inputs and KPIs that sector uses.
Limitations
- Every edition runs on synthetic sample data, so no figure here describes a real business.
- The tools read prepared files today rather than a live, scheduled feed.
What's next
- Scheduled ETL pipelines that load an Azure SQL Database, so dashboards refresh overnight.
- A restaurant-chain edition (covers, average cheque, labour per cover, kitchen capacity).
- A retail edition (footfall, conversion, basket size, stock cover).
- Power BI reports on the same star schema.
Run it on your own data
- In the browser (today)Free, no sign-up. What you enter stays on your device. Good for trying it and for small teams.
- On your files or databasePoint the same logic at your exports or a database view (PostgreSQL, SQL Server, Azure SQL or DuckDB), on your own machine or network.
- As a pipeline and warehouseA scheduled ETL job pulls from your systems (reservations, point of sale, inventory, payroll) into a star-schema warehouse, runs data-quality checks, and the tool or a Power BI report reads the result every morning.
How I'd set it up for you
I'd map your exports or database to the tool's model, package the job in a container that runs on your server or cloud account, add the checks your data needs, and hand over the code and a runbook. Your data stays on your systems. Get in touch if you'd like it fitted to your business.