Why should you care?

Swiggy’s daily GMV is SUM(order_total) for today — one number executives watch, not raw row export.

See it live — copy this example

Run in MySQL Workbench or the mysql CLI.

SELECT
  COUNT(*) AS order_count,
  SUM(total_inr) AS revenue_inr,
  AVG(total_inr) AS avg_order_inr,
  MIN(total_inr) AS smallest,
  MAX(total_inr) AS largest
FROM orders;

What happened?

• One result row summarizes the whole orders table.
• SUM and AVG ignore NULL totals if any.
• MIN/MAX show range of cart sizes for DataFlow.

Practice next

1. Insert varied order totals including one NULL (if column allows).
2. Run the aggregate SELECT.
3. Compare COUNT(*) vs COUNT(total_inr) if NULLs exist.
4. ROUND(AVG(total_inr), 2) for cleaner display.
5. Use IFNULL(SUM(total_inr),0) when no rows match WHERE.

Remember

Aggregates return single summary values. COUNT(*) counts rows; SUM/AVG work on numbers. Filter with WHERE before aggregating when possible.

DataFlow daily revenue tile

CEO dashboard runs one aggregate query every morning for yesterday’s SUM(total_inr).

Outcome: Finance trusts SQL numbers over spreadsheet exports.