Description\n-----------\n\nSQL (Structured Query Language) is a highly potent language used in the realm of databases and data analytics. It allows us to create, manipulate, and retrieve data stored in relational databases. While simple SQL commands can handle straightforward tasks, one must delve into advanced aspects such as multiple joins, subqueries, and set operations to unravel the full potential of SQL.\n\nMultiple Joins\n\nJoins are fundamental to SQL, as they enable us to combine rows from two or more tables based on related columns. Several types of joins exist, including INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.\n\nIn real-world scenarios, finding database schemas with multiple tables linked through relationships is common. In such cases, we often need to write SQL queries with multiple joins to fetch the required data.\n\nFor instance, consider a database for a bookstore with three tables: Books, Authors, and Publishers. If we want to get a list of books along with their author names and publishers, you would require multiple joins.\n\n``sql\nSELECT Books.title, Authors.name, Publishers.name\nFROM Books\nINNER JOIN Authors ON Books.author_id = Authors.id\nINNER JOIN Publishers ON Books.publisher_id = Publishers.id;\n`\n\nIn that query, we used two INNER JOIN operations to combine data from the three tables.\n\nSubqueries\n\nA subquery, also known as a nested query or inner query, is a query embedded within another SQL query. The result of the subquery can be used in the outer query. Subqueries can be used in SELECT, INSERT, UPDATE, and DELETE statements and also in conjunction with WHERE and HAVING clauses.\n\nSubqueries can prove powerful in many scenarios. For example, suppose we want to find books that are above the average price in our bookstore database. We could achieve this using a subquery.\n\n`sql\nSELECT title, price\nFROM Books\nWHERE price > (SELECT AVG(price) FROM Books);\n`\n\nIn this query, the subquery calculates the average book price, which the outer query then uses to filter books that are priced above average.\n\nSet Operations\n\nSQL also provides several set operations to combine rows from two or more tables, including UNION, UNION ALL, INTERSECT, and EXCEPT. These operations are instrumental when dealing with large databases where data is spread across multiple tables and we need to perform set-based operations.\n\nFor example, suppose we have two tables, _Books_2019_ and _Books_2020_, listing the books sold in the respective years. If we want to find books sold in both years, we can use the INTERSECT operation.\n\n`sql\nSELECT title FROM Books_2019\nINTERSECT\nSELECT title FROM Books_2020;\n``\n\nIn the above query, INTERSECT returns the common book titles sold in both 2019 and 2020.\n\nConclusion\n\nAdvanced SQL queries that involve multiple joins, subqueries, and set operations can be daunting at first glance. However, these incredibly powerful tools in our SQL toolkit enable us to craft complex data retrieval and manipulation commands. To truly excel in data analytics, mastering these aspects of SQL is not only beneficial but essential.\n\nRemember, practice is the key to mastering these advanced SQL concepts, like any other technical skill. Write queries, solve problems, make mistakes, and learn from them. Over time, you'll find yourself not only comfortable but proficient in creating intricate SQL queries.\n\nURL: https://mariadb.com/docs/server/reference/sql-structure/joins-subqueries-set