SQL Cheat Sheet: Joins, Window Functions & More

💡 Loved solving this SQL problem: “Find consecutive records…” At first, it looked simple—but the logic behind it is actually powerful and used in real-world scenarios like detecting trends, user behavior, or repeated actions. 🔍 The Problem: How do we identify consecutive entries in a dataset without manually checking each row? 🧠 My Approach: I used window functions like ROW_NUMBER() to create a sequence and compared it with actual values to detect patterns. 👉 Step-by-step: Assigned row numbers to each record Created a difference between row number & actual column Grouped similar differences to identify consecutive sequences 📌 Key Insight: Instead of checking row by row, we can use SQL logic to “group patterns” efficiently. 🎥 I’ve explained the full solution + query breakdown here: https://lnkd.in/gUbhzwhh If you're learning SQL, this is a must-know concept! Follow for more simple SQL breakdowns 🚀 #SQL #DataAnalytics #DataAnalyst #LearnSQL #SQLQueries #DataScience #TechLearning #CareerGrowth #Programming #CodeUnmasked7

Today I learned something interesting while solving SQL problem 👇 I used ROUND() thinking it will convert integer to decimal ❌ But I realized: ROUND() only formats output, it does NOT change datatype. 👉 Example: 5 / 2 = 2 5 / 2.0 = 2.5 Small learning, but important for avoiding wrong results. #SQL #LearningDaily

🚀 Day 27/100 – LeetCode SQL Challenge 📌 Problem Solved: Biggest Single Number Today’s challenge was about identifying a number that appears only once in a dataset and then finding the largest among them. 🔍 Key Concept: A single number means it appears exactly once. I used: ✔️ GROUP BY to group numbers ✔️ HAVING COUNT(num) = 1 to filter unique values ✔️ MAX() to find the largest among them 💡 What I Learned: Difference between WHERE and HAVING How to filter aggregated data using HAVING Writing optimized queries without unnecessary subqueries Importance of understanding problem keywords like "only once" 🧠 Approach: Count frequency of each number Filter numbers with count = 1 Return the maximum of those numbers 📈 This problem strengthened my understanding of aggregation and filtering in SQL — very useful! 🔥 Consistency is the key — one step closer to mastering SQL! #Day27 #LeetCode #SQL #100DaysOfCode #CodingJourney #PlacementsPreparation #DataAnalytics

🌅 Morning with Mistakes #1: The Comma That Broke My Query Started my morning with SQL practice… and a tiny mistake cost me more time than expected 👇 ❌ What went wrong: I forgot to add a comma between columns in the SELECT statement SELECT p.project_id ROUND(AVG(e.experience_years), 2) AS average_years At first glance, it looks correct… but SQL reads it as one expression → ❌ ERROR ✅ Fixed version: SELECT p.project_id, ROUND(AVG(e.experience_years), 2) AS average_years 💡 Morning lesson: • Never forget commas between columns • Small syntax errors can break the whole query • Debugging = patience + attention to detail ☀️ Day 1 of Morning with Mistakes — learning SQL the real way! #SQL #DataAnalytics #LearningInPublic #SQLMistakes #MorningLearning

🚀 Day 2 of My SQL Learning Journey Today I learned about the WHERE clause in SQL. 👉 WHERE is used to filter data based on specific conditions. Basic syntax: SELECT column_name FROM table_name WHERE condition; ✔ Helps in retrieving only the required data ✔ Can be used with operators like =, >, <, AND, OR 💡 Learning WHERE made me realize how powerful SQL is when working with large datasets. Excited to keep improving! 🔥 Next: INSERT statement 👀 #SQL #LearningJourney #Beginner #DataAnalytics #Day2 #LearnInPublic

Understanding the difference between RANK, DENSE_RANK and ROW_NUMBER in SQL can make a big difference in both interviews and real-world data analysis. A simple and clear explanation of SQL Ranking Functions is now live on CodeQueryHub. This video covers: • How RANK() works and why ranks get skipped • Difference between RANK() and DENSE_RANK() • How ROW_NUMBER() assigns unique values • Category-wise ranking using PARTITION BY • Key concepts often asked in SQL interviews This is Part 2 of the Window Functions series. Watch here: https://lnkd.in/gn7AkRRG #SQL #RankingFunctions #WindowFunctions #LearnSQL #SQLTutorial #SQLForBeginners #DataAnalytics #DataScience #DataAnalyst #DataEngineer #SQLQueries #SQLPractice #SQLLearning #Analytics #Database #DatabaseManagement #MySQL #PostgreSQL #OracleSQL #SQLServer #Programming #Coding #TechLearning #CareerGrowth #CodeQueryHub

Window Functions in SQL always felt confusing to me — especially OVER(), PARTITION BY and ORDER BY. So I tried breaking it down in the simplest way possible. A detailed explanation on all window functions will be in the next post. Till then, happy learning 🚀 #SQL #DataEngineering #WindowFunctions #openfornewopportunity #datalearning

🚀 Day 40 of My SQL Learning Journey Today I worked on a SQL problem involving aggregation and string manipulation 🔥 🔹 Problem: Group sold products by date and list them in sorted order 🔗 Problem Link: https://lnkd.in/gp6qVmNt 🔹 Solution: SELECT sell_date, COUNT(DISTINCT product) AS num_sold, GROUP_CONCAT(DISTINCT product ORDER BY product SEPARATOR ',') AS products FROM Activities GROUP BY sell_date; 🔹 Key Learning: Using COUNT(DISTINCT) for unique values Combining rows using GROUP_CONCAT() Sorting values inside aggregation 💡 SQL can generate clean reports directly from raw data! Consistency continues 🚀 #SQL #LeetCode #90DaysOfCode #DataAnalytics #CodingJourney

🔥 Post 1 (Day 2 – SELECT Statement Basics) 💡 Day 2 of My SQL Learning Journey Today I learned the most important part of SQL — SELECT statement 🚀 👉 SELECT statement is used to fetch data from a database. 📌 Basic syntax: SELECT column1, column2 FROM table_name; 📊 Example: SELECT name, age FROM students; ✨ This simply means: “students table se name aur age data lao” 💬 SQL ka real power yahi se start hota hai! 👉 Question: Have you tried writing your first SQL query yet? #SQL #DataAnalytics #LearningJourney #Day2 #BeginnerSQL

Understanding trends in data becomes much easier once LEAD and LAG functions are clear. A simple and practical explanation of SQL LEAD and LAG is now live on CodeQueryHub. This video covers: • What LEAD() and LAG() functions are • How to compare current, previous, and next rows • Using LAG() for past values and LEAD() for future values • Year-wise sales comparison • Percentage change calculation using window functions This is Part 3 of the Window Functions series. Watch here: https://lnkd.in/gJgefF-v #SQL #LeadLag #WindowFunctions #LearnSQL #SQLTutorial #SQLForBeginners #DataAnalytics #DataScience #DataAnalyst #DataEngineer #SQLQueries #SQLPractice #SQLLearning #Analytics #Database #DatabaseManagement #MySQL #PostgreSQL #OracleSQL #SQLServer #Programming #Coding #TechLearning #TrendAnalysis #GrowthAnalysis #CareerGrowth #CodeQueryHub