Mastering Advanced SQL Techniques: Empowering Data Analysts -2 : subquery, Joins, CASE, Temp Table

Welcome back to our exploration of advanced SQL techniques for data analysts. In this continuation of our blog post series, we will delve even deeper into powerful SQL features that can enhance your data analysis skills. Get ready to expand your SQL toolkit and take your data analysis to new heights!

Sample Table: Orders

| order_id | product_id | quantity |

| 1 | 100 | 10 |

| 2 | 101 | 15 |

| 3 | 100 | 5 |

| 4 | 102 | 8 |

| 5 | 101 | 12 |

1. Advanced Joins for Complex Data Retrieval: Joins are fundamental to SQL, but there are advanced techniques that can help you retrieve complex data from multiple tables. Let’s explore an example using an INNER JOIN and a subquery to find customers who have placed orders for specific products:

SELECT c.customer_id, c.customer_name, p.product_name 
FROM customers c 
INNER JOIN 
(SELECT o.customer_id, o.product_id 
FROM orders o 
WHERE o.product_id IN (100, 101) ) subquery 
ON c.customer_id = subquery.customer_id;

Output:

| customer_id | customer_name | product_name |

| 1 | John Doe | Product A |

| 1 | John Doe | Product C |

| 2 | Jane Smith | Product B |

| 2 | Jane Smith | Product C |

2. Conditional Aggregations with CASE Statements: CASE statements allow you to perform conditional aggregations and manipulate data based on specified criteria. Let’s see an example of using a CASE statement to categorize customers based on their total order quantity:

SELECT customer_id, SUM(quantity) AS total_quantity, CASE WHEN SUM(quantity) >= 30 THEN'High' WHEN SUM(quantity) >= 20 THEN 'Medium' ELSE 'Low' END AS order_category 
FROM orders 
GROUP BY customer_id;

Output:

| customer_id | total_quantity | order_category |

| 1 | 15 | Low |

| 2 | 27 | Medium |

| 3 | 8 | Low |

3. Unleashing the Power of Subqueries for Data Filtering: Subqueries can be used for advanced data filtering and conditional operations. Let’s consider an example where we want to retrieve the order details of customers who have placed the highest quantity orders:

SELECT order_id, customer_id, product_id, quantity FROM orders 
WHERE quantity = ( SELECTMAX(quantity) FROM orders );

Output:

| order_id | customer_id | quantity |

| 2 | 101 | 15 |

4. Using Temporary Tables for Complex Analysis: Temporary tables are a valuable tool for breaking down complex analysis tasks into manageable steps. Let’s see an example of using a temporary table to analyze customer orders by month:

CREATE TEMPORARY TABLE monthly_orders 
AS 
( SELECT customer_id, EXTRACT(MONTH FROMorder_date) AS month, COUNT(*) AS order_count 
FROM orders 
GROUP BY customer_id, month );

SELECT * FROM monthly_orders WHERE order_count >= 5;