SQL LEFT JOIN vs RIGHT JOIN: Understanding the Difference

Day 27/30 – SQL Challenge 🚀 Today’s challenge was all about identifying prime numbers using SQL — not something you see every day in database queries! Instead of traditional programming, I used recursive queries and logical filtering to: Generate numbers up to a limit Check divisibility conditions Filter out non-prime numbers Present results in a single line using a custom separator (&) 💡 Key takeaway: SQL isn’t just for data retrieval — with the right approach, it can handle complex logical problems too. This challenge really helped me think beyond basic queries and explore the power of recursive CTEs and conditional logic. #SQL #DataEngineering #ProblemSolving #30DaysOfSQL #LearningJourney

🚀 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

💡 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

WHERE vs HAVING in SQL Filtering data in SQL isn't always straightforward. Knowing when to use WHERE vs HAVING can save you from incorrect results. 🔹 WHERE filters rows before aggregation 🔹 HAVING filters results after aggregation 🔹 Use WHERE for raw data filtering 🔹 Use HAVING for grouped data filtering 💡 Master this difference to write cleaner and more accurate SQL queries. Save this post for your SQL learning journey. Follow JACOB JEYAKUMAR S for more updates #SQL #SQLServer #DataAnalytics #Database #DataEngineering #Programming #TechTips

🚀 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

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

9 Advanced SQL Window Function Tricks Most Developers Miss Most SQL developers are comfortable with functions like RANK(). But there are a few powerful window function techniques that rarely get discussed - and they can significantly improve how you write queries. In this presentation, I’ve covered: • The hidden default frame that can break your running totals • Why ROWS is often safer than RANGE • The EXCLUDE clause that almost no one talks about • Using FILTER() for cleaner conditional aggregation • Why LAST_VALUE() often gives unexpected results • How to chain window functions correctly using CTEs • Practical performance considerations when using window functions These are not just optimizations - they help you write more accurate, readable, and efficient SQL. I’ve kept the content concise and visual for easy understanding. Which of these concepts was new or most surprising to you? #SQL #DataAnalytics #DataEngineering #Programming #LearnSQL #CareerGrowth

SQL is the backbone of data work, but even the pros forget the specific order of a WINDOW FUNCTION or the difference between UNION and UNION ALL sometimes. I put together this comprehensive SQL Cheat Sheet to keep all the essentials in one place—from basic DML to advanced CTEs and Triggers. ✅ What’s inside: Joins & Set Operations Window Functions & Aggregations Date/Time formatting Transaction control Save this post 📌 so you can find it during your next project, and Tag a friend who’s currently learning SQL! #SQL #DataScience #DataAnalytics #Coding #Database #ProgrammingTips

🧠 SQL Cheat Sheet You’ll Actually Use SQL isn’t about syntax. It’s about how you think with data. 📌 Core Blocks: • SELECT → Get data • INSERT / UPDATE / DELETE → Manage data • CREATE / ALTER → Structure data • GRANT / REVOKE → Control access 🔗 JOINS = Real Power Combine tables → Get real insights 📊 Must Know: • COUNT, AVG, MAX • ROW_NUMBER, RANK 💡 You understand this, you can work with any database. 💬 Which part is tricky for you — JOINS or Window Functions? 👇 #SQL #DataAnalytics #LearnSQL #Programming #TechCareers

🧠 SQL Cheat Sheet You’ll Actually Use SQL isn’t about syntax. It’s about how you think with data. 📌 Core Blocks: • SELECT → Get data • INSERT / UPDATE / DELETE → Manage data • CREATE / ALTER → Structure data • GRANT / REVOKE → Control access 🔗 JOINS = Real Power Combine tables → Get real insights 📊 Must Know: • COUNT, AVG, MAX • ROW_NUMBER, RANK 💡 You understand this, you can work with any database. 💬 Which part is tricky for you — JOINS or Window Functions? 👇 #SQL #DataAnalytics #LearnSQL #Programming #TechCareers