Dinesh Kumar’s Post

A SQL query that calls itself! Sounds like a bug. It's actually a superpower: 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 𝗖𝗧𝗘𝘀! A recursive CTE is a Common Table Expression that selects from itself. Seems tricky, but it's actually not that difficult! Imagine you have this company hierarchy: Alice (CEO) ↳ Bob and Charlie report to Alice ↳ David and Eve report to Bob ↳ Frank and Grace report to Charlie You can build this entire corporate tree with SQL! Showing each employee and their level in the hierarchy. Behind the SQL scenes: 1️⃣ The base case gets the top of the hierarchy (Alice). 2️⃣ Then the CTE calls itself to find everyone reporting to her. 3️⃣ Each new “generation” of employees adds one more level. 4️⃣ The process continues until there are no more subordinates. That’s recursion! 🔄 The most powerful way to handle hierarchical data. 𝟭𝟬𝟬 𝗦𝗤𝗟 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤&𝗔 + 𝟯𝟬𝟬 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗘𝘅𝗮𝗺𝗽𝗹𝗲𝘀 + 𝗡𝗼𝘁𝗲𝘀 𝟭𝟬𝟬 𝗘𝘅𝗰𝗲𝗹 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤&𝗔 + 𝗡𝗼𝘁𝗲𝘀 + 𝗙𝗼𝗿𝗺𝘂𝗹𝗮 𝗦𝗵𝗲𝗲𝘁 𝟭𝟱𝟬 𝗣𝘆𝘁𝗵𝗼𝗻 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤&𝗔 (𝗡𝘂𝗺𝗣𝘆 + 𝗣𝗮𝗻𝗱𝗮𝘀 + 𝗠𝗮𝘁𝗽𝗹𝗼𝘁𝗹𝗶𝗯) 𝟭𝟬𝟬 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤&𝗔 + 𝗗𝗔𝗫 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁 + 𝗡𝗼𝘁𝗲𝘀 𝟭𝟬𝟬 𝗧𝗼𝗽 𝗛𝗥 𝗥𝗼𝘂𝗻𝗱 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤&𝗔 𝟭𝟬𝟬 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤&𝗔 + 𝗡𝗼𝘁𝗲𝘀 𝗥𝗲𝘀𝘂𝗺𝗲 𝗚𝘂𝗶𝗱𝗲 + 𝟳𝟬𝟬 𝗖𝗼𝗺𝗽𝗮𝗻𝘆 𝗦𝗶𝘁𝗲𝘀 𝗚𝗲𝘁 𝗔𝗰𝗰𝗲𝘀𝘀 𝗛𝗲𝗿𝗲: https://lnkd.in/dyBfCTjK #datascience #data #dataanalysis #sql #python #pandas #excel #powerbi

✅ Solved a SQL problem on LeetCode — Day 43 of my SQL Journey 💪 Text looks simple… until you try to handle every edge case ✍️ Today’s problem was about transforming text — capitalising the first letter of each word, while handling special cases like hyphens correctly. I used recursive logic and string operations to: • Break text into individual characters using recursive CTE • Track previous characters using window functions • Identify word boundaries and special cases • Apply conditional uppercase/lowercase transformations • Reconstruct the final string using GROUP_CONCAT What I practised: • Recursive CTEs for step-by-step processing • Using LAG() to track character-level context • Writing precise CASE conditions for formatting • Handling edge cases like hyphenated words What stood out — Text transformations aren’t just formatting… they’re about handling context. A single character can change the logic, and missing one condition can break everything. That’s where attention to detail matters most. SQL isn’t just for numbers and aggregations. It can handle complex text logic too. Consistent learning, one query at a time 🚀 #SQL #LeetCode #SQLPractice #DataAnalytics #LearningInPublic

📊 Just came across a really handy SQL Cheatsheet—perfect for quick revision and brushing up core concepts! It neatly covers: 🔹 DQL basics like SELECT, WHERE, GROUP BY, ORDER BY 🔹 Joins (INNER, LEFT, RIGHT, FULL) with simple visuals 🔹 Window functions like ROW_NUMBER(), RANK(), LAG(), LEAD() 🔹 Aggregations (SUM, AVG, COUNT, etc.) 🔹 DML & DDL operations (INSERT, UPDATE, DELETE, CREATE) What I like most is how it simplifies complex topics like joins and window functions into something visual and easy to recall. Whether you're preparing for interviews, working with data, or just revising fundamentals—this is a great quick reference. 💡 Tip: Don’t just memorize—practice writing queries to really understand how these concepts work together. #SQL #DataAnalytics #Learning #TechSkills #DataScience #Programming

Still getting confused by SQL Joins? You’re not alone! 🤯 Whether you are prepping for a technical data interview, debugging a complex query, or just starting your journey in tech, mastering how to combine tables is an absolute non-negotiable skill. Instead of memorizing endless text, visual learning is the way to go. This fantastic cheat sheet breaks down every major SQL Join using Venn diagrams, clear syntax, and real input/output examples. 📊 Here is your quick reference guide: 🔹 INNER JOIN: Returns only the matching rows from both tables. (The pure intersection!) 🔹 LEFT JOIN: Keeps everything from the left table (A), plus any matching rows from the right (B). 🔹 RIGHT JOIN: Keeps everything from the right table (B), plus any matching rows from the left (A). 🔹 FULL OUTER JOIN: The "everyone is invited" join. Returns all rows if there is a match in either the left or right table. 🔹 CROSS JOIN: The Cartesian product—every single row from Table A combined with every single row from Table B. #SQL #DataAnalytics #DataScience #DataEngineering #SoftwareEngineering #Database #Coding #TechCareers #LearnToCode #TechTips #Cheatsheet

🧠 20 SQL Concepts That ACTUALLY Matter If SQL feels confusing… It’s not hard ❌ You’re just looking at it all at once 😵💫 Let’s simplify it 👇 🔥 Core Concepts (Must Know) 👉 SELECT, WHERE, JOIN 👉 GROUP BY, ORDER BY 💡 These alone solve 70% of real problems ⚙️ Data Operations 👉 INSERT, UPDATE, DELETE 👉 TRANSACTION 💀 Basically: Create → Change → Destroy (developer life 😂) 🔗 Relationships & Structure 👉 PRIMARY KEY 👉 FOREIGN KEY 👉 INDEX 💡 These decide how FAST & CLEAN your data is 🧩 Advanced Concepts 👉 SUBQUERY, HAVING 👉 DISTINCT, UNION 👉 VIEW, CASE, TRIGGER ⚠️ This is where interviews get spicy 🌶️ 🎯 Reality Check: You don’t need 100 concepts… You need clarity on the RIGHT ones 💡 Pro Tip: Learn SQL like this: 👉 Concept → Practice → Real Problem 🚀 Once you master this… SQL goes from “confusing” → “powerful tool” 👉 Save this (your future self will thank you) 👉 Share with your coding gang 👉 Follow for more SQL breakdowns #SQL #DataAnalytics #DataScience #Coding #Programming #LearnSQL #TechSkills #InterviewPrep

**Day 9 of my 30 Days SQL Series 🚀** Today’s question was “Not Boring Movies” from LeetCode. At first, it looked like a simple filtering problem, but while solving it, I got stuck on a small concept. --- ### 💡 What the question was asking: We were given a table of movies with: * id * movie name * description * rating And we had to: 👉 select movies with **odd IDs** 👉 remove movies where description = **"boring"** 👉 sort the final result by **rating (highest first)** --- ### 😵💫 Where I got stuck: The condition for odd IDs was: `id % 2 = 1` I didn’t understand: 👉 why we are dividing by 2 👉 and what `%` actually does --- ### 🧠 What I understood: `%` is the **modulo operator**, which gives the remainder after division When we divide numbers by 2: * Even numbers → remainder = 0 * Odd numbers → remainder = 1 👉 So: `id % 2 = 1` means selecting **only odd IDs** --- ### ⚙️ Approach: * Used `% 2 = 1` to filter odd IDs * Removed rows where description = 'boring' * Sorted results using `ORDER BY rating DESC` --- ### 🧠 What I learned today: * `%` is not something to memorize, it’s a **logic to identify patterns** * Using 2 helps check even/odd, but `%` can be used with any number * Even simple questions can teach small but important concepts --- Today’s problem was easy, but it helped me understand the logic behind something I was just applying before. Learning step by step… 💪 #Day9 #SQL #LearningInPublic

SQL can seem intimidating at first, but most real-world queries rely on a few fundamental concepts. By mastering these 20 SQL concepts, you'll be ahead of many aspiring data analysts and developers: ✅ SELECT ✅ WHERE ✅ JOIN ✅ GROUP BY ✅ ORDER BY ✅ Subqueries ✅ HAVING ✅ INSERT / UPDATE / DELETE and more. Remember, don't try to learn everything in one day. Build queries, break them, debug them, and repeat. This practice is key to truly understanding SQL. Which SQL concept took you the longest to grasp? For me, JOINs and Subqueries were the toughest challenges. #SQL #DataAnalytics #DataEngineering #Database #LearningSQL #SQLQueries #TechSkills #Programming #CareerGrowth #DataAnalyst #SoftwareEngineering #BeginnersGuide

𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮 𝗧𝗲𝗺𝗽 𝗧𝗮𝗯𝗹𝗲? A Temporary Table is a table used to store data temporarily during a session.  • Created inside tempdb  • Automatically deleted when the session ends  • Useful for handling intermediate data in complex queries 𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗧𝗲𝗺𝗽 𝗧𝗮𝗯𝗹𝗲𝘀  1. 𝗟𝗼𝗰𝗮𝗹 𝗧𝗲𝗺𝗽 𝗧𝗮𝗯𝗹𝗲 (#𝗧𝗲𝗺𝗽𝗧𝗮𝗯𝗹𝗲)  • Prefixed with a single hash (#)  • Accessible only within the current session  • Automatically dropped when the session ends 🧠 Example: CREATE TABLE #Employees (   ID INT,   Name VARCHAR(50) );  2. 𝗚𝗹𝗼𝗯𝗮𝗹 𝗧𝗲𝗺𝗽 𝗧𝗮𝗯𝗹𝗲 (##𝗧𝗲𝗺𝗽𝗧𝗮𝗯𝗹𝗲)  • Prefixed with a double hash (##)  • Accessible across multiple sessions  • Dropped only when all sessions using it are closed 🧠 Example: CREATE TABLE ##Employees (   ID INT,   Name VARCHAR(50) ); 🔹 𝗪𝗵𝘆 𝗨𝘀𝗲 𝗧𝗲𝗺𝗽 𝗧𝗮𝗯𝗹𝗲𝘀? ✔ Break down complex queries into smaller steps ✔ Improve readability & debugging ✔ Store intermediate results ✔ Reuse data within a session ✔ Can improve performance in large data operations #Keys #Indexes #indexing #SqlIndex #SQL #DataEngineering #Data #DataEngineer #ETL #DataPipelines #CloudComputing #Python #TechCareers #Learning #SQLDeveloper #DataLife #TechHumor #SoftwareEngineering #Analytics #Programming #DatabaseDeveloper #Database #BusinessAnalytics #DataAnalytics #Upskilling #DBA

🚀 𝐒𝐐𝐋 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 𝐓𝐡𝐚𝐭 𝐄𝐯𝐞𝐫𝐲 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥 𝐒𝐡𝐨𝐮𝐥𝐝 𝐒𝐚𝐯𝐞 Most people learn SQL step by step… But struggle to connect everything together. This cheat sheet simplifies everything ↓ 𝐌𝐚𝐧𝐚𝐠𝐢𝐧𝐠 𝐓𝐚𝐛𝐥𝐞𝐬 (𝐏𝐚𝐠𝐞 𝟐) → CREATE, DROP, ALTER, TRUNCATE → Add/remove columns and constraints 𝐌𝐚𝐧𝐚𝐠𝐢𝐧𝐠 𝐓𝐫𝐢𝐠𝐠𝐞𝐫𝐬 (𝐏𝐚𝐠𝐞 𝟑) → BEFORE / AFTER events → INSERT, UPDATE, DELETE triggers 𝐌𝐚𝐧𝐚𝐠𝐢𝐧𝐠 𝐕𝐢𝐞𝐰𝐬 (𝐏𝐚𝐠𝐞 𝟒) → Create, update, and drop views → Recursive & temporary views 𝐌𝐨𝐝𝐢𝐟𝐲𝐢𝐧𝐠 𝐃𝐚𝐭𝐚 (𝐏𝐚𝐠𝐞 𝟓) → INSERT (single & multiple rows) → UPDATE with conditions → DELETE records 𝐐𝐮𝐞𝐫𝐲𝐢𝐧𝐠 𝐃𝐚𝐭𝐚 (𝐏𝐚𝐠𝐞 𝟔) → INNER, LEFT, RIGHT, FULL JOIN → CROSS JOIN for combinations 𝐂𝐨𝐧𝐬𝐭𝐫𝐚𝐢𝐧𝐭𝐬 (𝐏𝐚𝐠𝐞 𝟕) → PRIMARY KEY, FOREIGN KEY → UNIQUE, CHECK, NOT NULL 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫𝐬 (𝐏𝐚𝐠𝐞 𝟖) → UNION, INTERSECT, MINUS → LIKE, IN, BETWEEN, NULL checks 𝐖𝐡𝐲 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫𝐬: Because SQL is not about syntax It’s about understanding how data works 𝐓𝐫𝐮𝐭𝐡: Anyone can write a query But not everyone can optimize it 𝐓𝐢𝐩: Focus on joins Understand constraints Practice real-world queries That’s what gets you hired Save this for quick revision Follow me for more simple and practical tech content #SQL #DataEngineering #DataAnalytics #Database #TechCareers #Learning #Programming #BigData #Developers #CareerGrowth

Most developers write SQL in one order—but the database executes it in another. Understanding SQL’s logical execution order is the key to writing better queries, debugging faster, and mastering advanced SQL. 🔄 SQL Execution Order: 1. FROM / JOIN – Build the initial dataset 2. WHERE – Filter rows 3. GROUP BY – Group the filtered data 4. HAVING – Filter grouped results 5. SELECT – Choose the columns to return 6. DISTINCT – Remove duplicates 7. ORDER BY – Sort the final result 8. LIMIT / OFFSET – Return only the required rows 💡 Why this matters: * Explains why aliases don’t work in WHERE * Helps you debug GROUP BY and HAVING issues * Makes query optimization much easier * Improves your confidence in writing complex SQL If you’ve ever wondered why SQL behaves “weirdly,” this execution order is usually the answer. Save this for your next SQL interview or debugging session. 📌 Save this post 🔁 Repost to help others 👨💻 Follow Abhishek Sharma for more such content #SQL #Database #DataEngineering #BackendDevelopment #Programming #SoftwareEngineering #LearnSQL #TechTips #Coding