OUTER JOINs allow you to retrieve all records from one or both tables in a join operation, even when there are no matches.

Types of OUTER JOINs:

• LEFT JOIN - Keep all records from left table
• RIGHT JOIN - Keep all records from right table
• FULL OUTER JOIN - Keep all records from both tables

Basic Syntax:

SELECT columns
FROM table1
LEFT JOIN table2
ON table1.column = table2.column;

Key Differences from INNER JOIN:

• Returns non-matching rows
• NULL values for non-matches
• More comprehensive results
• Better for data analysis

Let's start with a LEFT JOIN to find all customers and their orders (if any).

Write a query that gets:

• Customer name and email
• Order total (may be NULL)
• From customers LEFT JOIN orders
• Order by customer name

Tips:

• LEFT table (customers) keeps all records
• RIGHT table (orders) provides matches
• NULL indicates no matching order
• Consider using COALESCE for NULLs

OUTER JOINs are perfect for finding missing relationships.

Write a query that finds:

• All customers who have never placed an order
• Show their name and email
• Using LEFT JOIN and WHERE

Use Cases:

• Finding inactive customers
• Identifying orphaned records
• Data quality checks
• Marketing analysis

Note: WHERE clause with NULL check finds missing relationships.

We can chain multiple OUTER JOINs together.

Write a query that gets:

• Product name
• Category name (may be NULL)
• Count of orders (may be 0)
• Using appropriate LEFT JOINs

Advanced Concepts:

• Chaining multiple joins
• Handling multiple NULL possibilities
• Aggregating with outer joins
• Proper join order

Remember: Join order matters with OUTER JOINs.

Let's see the difference between INNER and LEFT JOIN.

Write two queries: 1. INNER JOIN products and orders 2. LEFT JOIN products and orders Compare the counts using UNION ALL

Learning Points:

• INNER JOIN shows only matches
• LEFT JOIN shows all left records
• Difference reveals missing data
• Important for data analysis

This helps understand when to use each type.

Use OUTER JOINs for comprehensive data analysis.

Write a query that shows:

• Category name
• Total products in category
• Products with orders
• Products without orders
• Using LEFT JOINs

Analysis Goals:

• Category performance
• Product engagement
• Missing relationships
• Data completeness

This provides valuable business insights.

Combine OUTER JOINs with other SQL features.

Write a query that:

• Shows customer order summary
• Includes total orders and total spent
• Shows last order date
• Includes customers with no orders
• Orders by total spent (highest first)

This combines:

• LEFT JOIN
• Aggregation
• Date functions
• Sorting
• NULL handling

A real-world reporting query.