Why should you care?

A messy schema makes every feature slower to ship. DataVerse needs clear Customer–Order–OrderItem–Product boundaries.

See it live — copy this example

Run in SQL Server Management Studio (SSMS) or Azure Data Studio.

USE DataVerse;
-- Core OLTP sketch
-- Customers (1) --- (many) Orders (1) --- (many) OrderItems (many) --- (1) Products
SELECT
    t.name AS TableName,
    SUM(p.rows) AS ApproxRows
FROM sys.tables t
JOIN sys.partitions p ON p.object_id = t.object_id AND p.index_id IN (0,1)
WHERE t.is_ms_shipped = 0
GROUP BY t.name
ORDER BY t.name;

What happened?

• The comment documents the intended shape.
• The catalog query inventories user tables and rough row counts — a design review checklist starter.

Practice next

1. Sketch Customer/Order/Item/Product on paper.
2. Confirm each table has a primary key.
3. Run the inventory query in your database.
4. Add dbo.Addresses with FK to Customers.
5. Document cascade rules next to each FK in a README.

Remember

Design around clear entities and keys. Normalize by default; denormalize with evidence. Review row counts and relationships often.

DataVerse OLTP blueprint

Architects lock the order schema before Black Friday features.

Outcome: Checkout, inventory, and invoice teams share one model.