CASE WHEN Examples in SQL

What CASE WHEN does

Create conditional labels, buckets and flags. SQL syntax can vary by database, but the pattern below is a useful starting point for reports and analysis.

Syntax or pattern

CASE WHEN condition THEN result ELSE other_result END

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5 practical examples

Create order size buckets

Label orders as small, medium or large.

SELECT order_id, total_amount,
  CASE
    WHEN total_amount >= 1000 THEN 'Large'
    WHEN total_amount >= 250 THEN 'Medium'
    ELSE 'Small'
  END AS order_size
FROM orders;

CASE creates readable categories for reports.

Flag overdue tickets

Mark tasks that are past their due date.

SELECT ticket_id, due_date,
  CASE WHEN due_date < CURRENT_DATE THEN 'Overdue' ELSE 'On track' END AS status_flag
FROM tickets;

This turns date logic into a simple label.

Group customers by activity

Classify customers by order count.

SELECT customer_id, order_count,
  CASE WHEN order_count >= 10 THEN 'Frequent' ELSE 'Occasional' END AS customer_type
FROM customer_summary;

Useful for segmentation and dashboards.

Conditional sales total

Sum sales only for completed orders.

SELECT SUM(CASE WHEN status = 'Completed' THEN total_amount ELSE 0 END) AS completed_sales
FROM orders;

CASE inside SUM is a common reporting pattern.

Replace null-like labels

Create a clean label for missing assignments.

SELECT ticket_id,
  CASE WHEN agent_id IS NULL THEN 'Unassigned' ELSE 'Assigned' END AS assignment_status
FROM tickets;

This makes operational reports easier to scan.

Common mistakes to avoid

Forgetting that SQL dialects vary across PostgreSQL, SQL Server, MySQL, BigQuery and SQLite.
Using SELECT * in production reports when only a few columns are needed.
Not checking join keys, duplicate rows or NULL values before trusting results.

FAQ

Will this SQL work in every database?

The idea is portable, but function names and date syntax may vary. Check your database dialect if a function is not recognized.

Should I use this in a report query?

Yes, if the pattern matches the business question and you have checked filters, joins and row counts.

Why does my result have too many rows?

The most common reasons are duplicate join keys, missing filters or grouping at the wrong level of detail.

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