Optimizing a Slow SQL Query | Dataford Interview Questions

Describe a scenario where you had to optimize a slow-running SQL query and how you approached it.

For a hands-on PostgreSQL response, use the provided customers and orders tables to produce the optimized result described below.

Output

One row per customer region and calendar month
Columns: region, month, and completed_revenue
Include completed orders from January 1, 2025 through March 31, 2025, excluding unmatched customers
Sort by region ascending, with NULL regions first, then month ascending

customers

orders

Column	Type	Description
order_idPK	INT	Unique order identifier
customer_id	INT	Customer associated with the order
order_date	DATE	Order creation date
status	VARCHAR(20)	Order processing status
amount	NUMERIC(12,2)	Order revenue amount

Your question is Optimizing a Slow SQL Query. Start with the requirements and the two tables in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Describe a scenario where you had to optimize a slow-running SQL query and how you approached it.

For a hands-on PostgreSQL response, use the provided customers and orders tables to produce the optimized result described below.

One row per customer region and calendar month
Columns: region, month, and completed_revenue
Include completed orders from January 1, 2025 through March 31, 2025, excluding unmatched customers
Sort by region ascending, with NULL regions first, then month ascending

customers

orders

Column	Type	Description
order_idPK	INT	Unique order identifier
customer_id	INT	Customer associated with the order
order_date	DATE	Order creation date
status	VARCHAR(20)	Order processing status
amount	NUMERIC(12,2)	Order revenue amount

Your question is Optimizing a Slow SQL Query. Start with the requirements and the two tables in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.