Why should you care?

Data reconciliation — compare two lists (source vs target) and see extras on either side in one pass.

See it live — copy this example

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

USE DataVerse;
IF OBJECT_ID(N'dbo.PosSales', N'U') IS NOT NULL DROP TABLE dbo.PosSales;
IF OBJECT_ID(N'dbo.OnlineSales', N'U') IS NOT NULL DROP TABLE dbo.OnlineSales;
CREATE TABLE dbo.PosSales (Sku VARCHAR(32) PRIMARY KEY, Qty INT);
CREATE TABLE dbo.OnlineSales (Sku VARCHAR(32) PRIMARY KEY, Qty INT);
INSERT INTO dbo.PosSales VALUES ('A', 5), ('B', 2);
INSERT INTO dbo.OnlineSales VALUES ('B', 3), ('C', 4);
SELECT
    COALESCE(p.Sku, o.Sku) AS Sku,
    p.Qty AS PosQty,
    o.Qty AS OnlineQty
FROM dbo.PosSales AS p
FULL OUTER JOIN dbo.OnlineSales AS o ON o.Sku = p.Sku;

What happened?

• Sku A is POS-only, C is online-only, B is both.
• FULL OUTER JOIN surfaces all three cases for a stock sync review.

Practice next

1. Create the two sales tables and run the join.
2. Identify rows where PosQty IS NULL or OnlineQty IS NULL.
3. Add a computed difference column ISNULL(o.Qty,0) - ISNULL(p.Qty,0).
4. Filter WHERE p.Sku IS NULL OR o.Sku IS NULL for mismatches only.
5. Add a third channel table later with a different pattern.

Remember

FULL OUTER keeps unmatched rows from both sides. Great for reconcile / diff reports. COALESCE the business key in the SELECT list.

POS vs online qty reconcile

Nightly job diffs DataVerse POS and online quantities.

Outcome: Ops investigates SKUs present in only one channel.