Joining tables in SQL is a fundamental operation for combining data from different tables. A join on multiple columns refines this process by specifying matching criteria across multiple columns. Instead of matching on a single column, you're looking for rows where multiple columns have matching values. This is essential for scenarios where a single column isn't sufficient to uniquely identify the relationship between tables. For example, if you have a 'Customers' table and an 'Orders' table, you might need to join them based on both the customer ID and the order ID to retrieve all order details for a specific customer. This approach ensures you retrieve only the relevant data, avoiding ambiguity and inaccuracies.Multiple-column joins are particularly useful when dealing with composite keys or when you need to link data based on multiple attributes. For instance, in an inventory system, you might have a 'Products' table and a 'Suppliers' table. To find all products supplied by a specific supplier, you'd need to join on both the product ID and the supplier ID. This approach ensures you retrieve only the products from the desired supplier.Understanding how to join on multiple columns is a critical skill for any SQL developer. It allows for complex data retrieval and manipulation, enabling the creation of sophisticated queries that extract meaningful insights from relational databases. The ability to specify multiple join conditions ensures that the results are precise and relevant, avoiding extraneous or incomplete data.