SQL Practice on LeetCode: Day 15 of DSA Journey

🚀 Day 49 | LeetCode Learning Journal Today I solved Rank Scores using SQL. This problem introduced me to ranking functions and how to handle duplicate values efficiently in databases! 🔑 Key Points: • Used DENSE_RANK() for ranking • Applied ORDER BY to rank scores in descending order • Understood difference between RANK() and DENSE_RANK() • Ensured no gaps in ranking 🌱 What I Learned: • How ranking functions work in SQL • Handling duplicates while assigning ranks • Writing cleaner queries using window functions • Importance of choosing the right ranking method #LeetCode #100DaysOfCode #DSA #CodingJourney #SQL #Database #Day49 🚀

🚀 Day 16/30 – SQL Challenge 🔹 Problem: Find the first year each product was sold along with its details. 🔹 Approach: Used MIN(year) with a JOIN to get the correct records. Also explored using ROW_NUMBER(). 🔹 Learning: Avoid tuple IN queries and prefer JOINs or window functions for better results. #SQL #LeetCode #Day16 #CodingJourney #ProblemSolving #SDE

🚀 Day 19/30 of my SQL Problem Solving Challenge 💻 Problem Statement: Find total distance traveled by each user and sort them by highest distance. If distances are equal, sort by name. 🧠 Approach: Used LEFT JOIN to include all users, SUM() with GROUP BY to calculate total distance, and ORDER BY for sorting. Also handled NULL values using COALESCE. ✨ Key Learning: Break the problem into steps, join data, group it, apply aggregation, then sort. Also learned a new function COALESCE, which replaces NULL values by returning the first non-null value (used it here to convert NULL distance into 0). #SQL #30DaysOfSQL #MYSQL #CodingJourney #SDE #ProblemSolving #Streak #DailyLearning

🚀 Day 50 | LeetCode Learning Journal Today I solve Delete Duplicate Emails using SQL. This problem helped me understand how to clean duplicate data efficiently in databases! 🔑 Key Points: • Used SELF JOIN to identify duplicate emails • Compared records using id to keep the smallest one • Deleted unwanted duplicate rows • Explored alternative solution using GROUP BY 🌱 What I Learned: • How to remove duplicate records in SQL • Importance of data cleaning in real-world applications • Working with self joins for comparison • Writing efficient delete queries #LeetCode #100DaysOfCode #DSA #CodingJourney #SQL #Database #Day50 🚀

🚀 Day 18 of Learning SQL Today I explored Subqueries in SQL and understood how powerful they are when dealing with complex conditions. Here’s what I learned: 🔹 Subqueries are queries written inside another query 🔹 They are useful when we need to find unknown values or conditions 🔹 Help in breaking complex problems into smaller, manageable parts 🔹 Commonly used with SELECT, WHERE, and FROM clauses 💡 Key Insight: Whenever we don’t know an exact value or condition beforehand, we can use a subquery to dynamically fetch it and use it in the main query. This concept made me realize how SQL can solve real-world problems efficiently by combining multiple queries. Step by step, building stronger SQL skills! 💪 #Day18 #SQL #Subqueries #LearningJourney #DataAnalytics #Programming #Database

🚀 Day 8/100 – Combining SQL Logic & String Problem Solving Today’s learning was a mix of SQL queries and DSA string problems, helping me strengthen both database concepts and coding logic. 💻 What I worked on: 🗄️ SQL Practice Solved queries involving aggregation and filtering Used functions like: MAX() ROUND() Applied subqueries to fetch precise results 📌 Example: Finding maximum latitude under a condition Extracting corresponding longitude using subqueries 💻 DSA (Strings) on LeetCode 1️⃣ Length of Last Word Traversed string from end Handled trailing spaces efficiently 2️⃣ Find First Occurrence (strStr) Implemented substring matching Understood basic pattern searching 🧠 Key Learning: ✔ SQL helps in extracting meaningful insights from structured data ✔ String traversal techniques are important for interviews ✔ Edge case handling (spaces, substrings) improves problem-solving 📈 Progress: Continued consistency in daily coding Strengthening fundamentals in both SQL & DSA 🎯 Next Goals: Move to medium-level problems Learn advanced SQL queries (JOINs, GROUP BY) Explore efficient string algorithms Building consistency one day at a time 🚀 #Day8 #100DaysOfLearning #SQL #DSA #LeetCode #Strings #ProblemSolving #CodingJourney

🚀 Day 51 | LeetCode Learning Journal Today I solved Rising Temperature using SQL. This problem helped me understand how to compare data across rows and work with dates effectively! 🔑 Key Points: • Used SELF JOIN to compare current and previous day • Applied DATEDIFF() to ensure consecutive dates • Checked temperature increase condition • Explored window function (LAG) as an alternative 🌱 What I Learned: • How to compare rows within the same table • Working with date functions in SQL • Importance of handling time-based data • Writing efficient queries using joins and window functions #LeetCode #100DaysOfCode #DSA #CodingJourney #SQL #Database #Day51 🚀

🚀 Day 9/30 of My LeetCode Journey (SQL Focus) Another day, another step towards mastering SQL! 📊💻 🔹 **SQL Problem of the Day** 👉 *Delete Duplicate Emails* Given a `Person` table, write a query to delete all duplicate emails, keeping only the record with the smallest `id`. 💡 *Key Concept:* Identifying duplicates using self-join / subquery and removing extra records using `DELETE`. Learning not just how to fetch data, but also how to clean and manage it efficiently 🔥 Day 9 done ✅ #LeetCode #30DaysChallenge #SQL #CodingJourney #Consistency #DataCleaning #ProblemSolving #Learning

🚀 Day 36 of My SQL Learning Journey Today I worked on a challenging SQL problem involving consecutive records and learned an important lesson along the way 🔥 🔹 Problem: Find records where people count is ≥ 100 for at least 3 consecutive entries 🔗 Problem Link: https://lnkd.in/gNBER5CQ 🔹 Final Solution: WITH temp AS ( SELECT id, visit_date, people, id - ROW_NUMBER() OVER (ORDER BY id) AS grp FROM Stadium WHERE people >= 100 ) SELECT id, visit_date, people FROM temp WHERE grp IN ( SELECT grp FROM temp GROUP BY grp HAVING COUNT(*) >= 3 ); 🔹 Key Learning 💡: The approach was to use ID-based grouping, because the problem depends on consecutive entries (IDs), not consecutive dates. 🔹 Concepts Used: ROW_NUMBER() for sequence handling Grouping consecutive records Window functions + aggregation 💡 Debugging mistakes helped me understand the problem more deeply than just solving it! Consistency continues 🚀 #SQL #LeetCode #WindowFunctions #ProblemSolving #90DaysOfCode #CodingJourney

🤔 Ever wondered how SQL actually works behind the scenes? It all comes down to 5 powerful command types: ✨ DDL – Structure your database ✨ DML – Add & modify data ✨ DCL – Control access ✨ TCL – Manage transactions ✨ DQL – Fetch data 💡 Think of it like this: Structure ➝ Data ➝ Security ➝ Control ➝ Query If you master these, you're already ahead of most beginners 🚀 🌐 www.skillversed.com 📩 support@skillversed.com 📌 Save this cheat sheet 💬 Which one confuses you the most? 🔁 Share with your coding buddy #SQLBasics #LearnToCode #DataEngineer #TechLearning #SQLTips #CodingJourney #DatabaseManagement #Skillversed