Ecommerce storefront
A year of orders across five joined tables, with a real Q4 peak and totals that reconcile to the cent.
An online retailer's 2025: customers, a 300-SKU catalogue, orders, line items, and reviews. Every order total is exactly the sum of its own line items, so the joins and the arithmetic both hold when you check them. Demand rises into November and December because there are more orders, not because the orders got bigger, which is how real seasonality works.
- ecommerce
- retail
- star schema
- seasonality
Explore
Every table, profiled
Each column's type, spread, empties and most common values, measured from the CSVs in the download. Switch to the first rows to see the data exactly as it sits in the file.
5 tables
order_items.csv
31,000 rows · 6 columns · 2 foreign keys
Keys
Every join resolves
5 foreign keys, 82,703 references checked against the table each one points at. None points at a row that does not exist.
order_items
- order_idorders.order_id31,000 rows checked0 orphans
- product_idproducts.product_id31,000 rows checked0 orphans
orders
- customer_idcustomers.customer_id11,081 rows checked0 orphans
reviews
- product_idproducts.product_id4,811 rows checked0 orphans
- customer_idcustomers.customer_id4,811 rows checked0 orphans
Checks
What we checked
- 0 orphaned foreign keys across all 5 relationships
- 0 orders dated before their customer signed up
- order_total equals the sum of its line items, exactly, for every order
- 0 products priced at or below cost (margins run 22% to 64%)
- Ratings are J-shaped (57% five-star, 7% one-star), not uniform
- Top 10% of customers place 29.5% of orders, a realistic Pareto tail
- 59% of prices end in .99, as real catalogues do
- Every city belongs to its country (London and Newcastle appear under two, correctly)
The same checks ship in the zip as INTEGRITY.txt, so you can rerun them in any SQL engine. How we verify
Questions
Worth asking it
- 1Which category carries the best margin, and is it the one selling most?
- 2How much of revenue comes from the top 10% of customers?
- 3Do low-rated products actually get returned more often?
- 4What does the Q4 lift look like split by channel?
Use it
Take it, or make one shaped like yours
Rebuild it byte for byte
The zip includes schema.yaml. Run misata generate --config schema.yaml with seed 20260721 and you get the same rows.
Your own tables, your own numbers
Describe the data you need in Studio and get connected tables with the totals you state, profiled like this and checked before you download.
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Fully synthetic. No real person, company or transaction is represented, and no production data was read to make it. CC0: use it anywhere, no attribution needed.