Understanding SQL Window Functions with Real-World Scenarios

🧠 SQL Problem That Looks Simple… But Isn’t 👇 There’s a queue of people waiting to board a bus with a weight limit of 1000 kg. The goal? 👉 Find the last person who can board without exceeding the limit. At first glance, it feels like a simple filter problem. But the moment you think deeper, you realize: 👉 This is about running totals (cumulative sum) So instead of looping row by row, I used a window function, 💡 Key Insight: Compute cumulative weight using SUM() OVER (ORDER BY turn) Filter valid rows (<= 1000) Pick the last feasible person 🔥 What I learned: Window functions can replace complex loops Many “greedy” problems translate neatly into SQL Thinking in terms of running aggregates is powerful Curious — how would you approach this without window functions? 🤔 #SQL #DataAnalytics #LearningInPublic #DataScience #LeetCode

Turning math into SQL logic Calculated distance between two points using SQL, using simple functions like SQRT() and POWER() #SQL #DataAnalytics #DataAnalyst #BusinessIntelligence #DataScience #Analytics #TechCareers #Math #EnjoyLearning

#Day_33 of My Learning Journey 🚀 | SQL Aggregate Functions Today I explored powerful SQL Aggregate Functions to analyze data efficiently 📊 🔹 Learned functions: • MAX() – highest value • MIN() – lowest value • COUNT() – total records • SUM() – total marks • AVG() – average marks • Using BETWEEN for range filtering #Day33 #SQL #Database #LearningJourney #Coding #DataAnalysis

SQL is more than just code; it’s a tool for curiosity. 🔍 I just wrapped up a deep dive into SQL foundations. Instead of just following tutorials, I focused on real-world applications—asking questions of the data and building queries to find the answers. What I’ve been building: ✅ Multi-table JOINs to calculate total revenue. ✅ GROUP BY & COUNT logic to track yearly order volumes. ✅ Data segmentation using CASE statements for payment analysis. ✅ Clean reporting using DISTINCT and specific filtering. The goal wasn't just to get the query to "run," but to make it efficient and meaningful. Next stop: Window Functions and Subqueries! 🚀 #DataScience #SQL #LearningPublic #DataAnalyst #TechJourney

📊 SQL Joins Cheat Sheet — simplified for data learners! I created a clean, single-page visual guide covering INNER, LEFT, RIGHT, FULL, CROSS, and SELF joins. It includes intuitive diagrams, easy SQL syntax, quick explanations, real-world use cases, and when not to use each join. Plus, a comparison table and pro tips on performance, NULL handling, and common mistakes. The goal: make joins easy to understand at a glance — not just memorize. Perfect for beginners and a quick refresher for intermediates. Save it, share it, and level up your SQL skills 🚀 #SQL #DataAnalytics #LearnSQL #DataScience #Analytics #DataEngineer #TechSkills #Database #CareerGrowth #SQLCheatSheet

🚀 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

Storing and retrieving data is a fundamental skill for any developer or data enthusiast, and understanding SQL JOINs is absolutely critical. 💡 Struggling to visualize how INNER, LEFT, RIGHT, FULL OUTER, or CROSS JOINs actually work? This handy cheat sheet breaks down each type with clear: 1.Venn Diagram representations – A classic visual for set operations. 2.SQL Syntax examples – See exactly how to write the query. 3. Sample Tables (Table A & Table B) – Clear input data. 4.Resulting Tables – Instant visualization of the output. Whether you're brushing up on your skills or just starting your SQL journey, save this infographic for quick reference! Let's get joining! #SQL #Database #DataScience #DataAnalytics #SoftwareEngineering #DataTutorial #CheatSheet #LearnToCode

Day by day, I’m building a stronger foundation in SQL. Today’s session was packed with powerful concepts: - Alerts - CTE (Common Table Expressions) - Views - Subqueries - Scalar functions Each topic is helping me think more efficiently when working with data and writing optimized queries. Still learning, still improving. #SQL #DataLearning #Analytics #LearningJourney

One SQL concept that completely changed my analysis game 👇 WINDOW FUNCTIONS Instead of complex subqueries, I now use: ROW_NUMBER() RANK() LAG() / LEAD() Used it recently to: ✔ Identify top customers ✔ Track user behavior over time ✔ Analyze drop-offs If you're learning SQL — master this early. #SQL #DataAnalytics #Learning

🚀 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