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can even solve mathematical problems in SQL. They’re flexible but can also be tricky, especially with large datasets. #SQL #DataAnalytics #RecursiveCTE #HierarchicalData #SQLChallenge #LearningJourney #TechJourney #AdvancedSQL #DataEngineering.

an employee hierarchy, showing how employees report to managers. 2. Calculating a Factorial Using Recursive CTE – As a fun exercise, I used a recursive CTE to calculate the factorial of a number. 💬 Recursive CTEs are extremely useful for navigating hierarchical data and.

I took on the challenge of recursive Common Table Expressions (CTEs)—a powerful tool for handling hierarchical or self-referencing data structures like organizational charts or category trees. 💻 Today's Tasks:. 1. Building an Employee Hierarchy – I used a recursive CTE to model.

Day 18/30 of My SQL Challenge: Recursive CTEs & Hierarchical Data 🔄🔍. I wasn't able to share yesterday's own. So I will be sharing two challenge today yesterday's and today's own respectively.

📊Day 17/30 of. 💻 Today's Tasks:. 1. Creating a Temporary Table for High-Value Orders – I used a temporary table to store data for orders greater than $1,000 and performed additional analysis on it. 2. Adding an Index to Improve Query Performance . #SQL #DataAnalytics.

📊Day 17/30 of My SQL Challenge: Temporary Tables & Indexes 🏗️🚀. As I progress through my SQL challenge, today I tackled temporary tables and indexes—both essential for improving query performance and managing complex data operations efficiently.

each product over time using the ROW_NUMBER() function. 💬 Window functions are game changers when you need to perform advanced analysis across rows without grouping them. They’re perfect for rankings, running totals, and so much more.#SQL #DataAnalytics #Ranking #SQLChallenge.

💻 Today's Tasks:. 1. Ranking Products by Sales in Each Category – I used window functions to rank products based on their sales quantity within each category. Here’s the query:. 2. Calculating Running Total of Sales by Date – I also calculated a running total of sales for.

✨Day 16/30 of My SQL Challenge: Window Functions & Advanced Ranking 🚀📊. Today, I dived into one of the most powerful features in SQL—window functions! They allow for more flexible data analysis without grouping, which makes them a go-to tool for complex calculations.

2. Calculating the Number of Days Since Each Sale – I also wrote a query to calculate how many days ago each sale happened. Here’s the solution:. #SQL #DataAnalytics #StringFunctions #DateFunctions #DataCleaning #SQLChallenge #LearningJourney #TechJourney #DataWrangling.

Day 15/30 of My SQL Challenge: String Functions & Date Manipulations 🧑‍💻📅. 💻 Today's Tasks:. 1. Extracting Initials from Product Names – I created a query to extract the initials of each product name using string functions.

2. Top-Selling Products – I also found products that have made at least $5,000 in total sales. Here’s the query:. Understanding joins and aggregations are key to making data more meaningful and driving business insights. 🎯. #SQL #DataAnalytics #DataScience #SQLChallenge #Joins.

Day 14/30 of My SQL Challenge. 💻 Today's Tasks:. 1. Total Sales Revenue per Category – I wrote a query to calculate the total sales revenue for each product category by joining products and sales tables.

2. Get products that have never been ordered. Write a query using a subquery to return products from the products table that have never been ordered. #SQL #DataAnalysis #DataAnalytics #DataScience #CodingChallenge.

orders table:.order_id (INT), product_id (INT), quantity (INT), order_date (DATE), customer_id (INT). ✨ Tasks:. 1. Find the most expensive product in each category. Write a query to return the product with the highest price in each category using a correlated subquery.