Nick Holt’s Post

SQL Cheatsheet for data analysts :- The infographic neatly organizes everything into six sections: 1. Basics :- ( select, rename, all columns ) 2. Filtering Data :- ( WHERE, AND, LIKE ) 3. Aggregations :- ( COUNT, SUM, GROUP BY, HAVING ) 4. Joins :- ( INNER, LEFT ) 5. Useful Functions :-( string, date, CASE ) 6. Data Analyst Essentials :- ( LIMIT, DISTINCT, window functions ) This kind of short revision sheet helps much more than reading long notes again and again. Comment SQL if you want more posts like this on interview prep, cheatsheets, and practical data engineering learning. #SQL #DataEngineering #DataAnalyst #InterviewPreparation #LearnSQL #Database #TechCareers #DataEngineer #CareerGrowth

A small SQL habit that made a big difference in my work: In my early days as a Data Analyst, I focused on getting the correct output. Over time, I realized that how you write your queries matters just as much as the result. One approach that really improved my workflow: 👉 Using CTEs (Common Table Expressions) Why I prefer them: • Break down complex logic into clear steps • Make queries easier to read and debug • Improve collaboration with team members • Reduce dependency on deeply nested subqueries Clean SQL isn’t just about readability—it directly impacts efficiency and scalability. 💡 Writing better queries = better analysis. What’s one SQL practice that improved your workflow? #SQL #DataAnalytics #DataAnalyst #TechSkills #CareerGrowth #Learning #DataDriven

𝗠𝗮𝘀𝘁𝗲𝗿 𝗦𝗤𝗟 𝗟𝗶𝗸𝗲 𝗮 𝗣𝗿𝗼 — 𝗢𝗻𝗲 𝗤𝘂𝗲𝗿𝘆 𝗮𝘁 𝗮 𝗧𝗶𝗺𝗲 In today’s data-driven world, SQL is not just a skill — it’s a superpower. Whether you're aiming for a Data Analyst role or leveling up your career, SQL is your foundation. But let’s be real — learning SQL isn’t about memorizing syntax. It’s about solving real problems, thinking logically, and writing efficient queries. That’s exactly why I started this SQL Challenge series. Every day, we tackle questions that push your thinking to the next level. From basics to advanced concepts, from simple SELECTs to complex window functions — this journey is designed to make you confident with data. Consistency is the key 🔑 Even one question a day can transform your skills over time. So if you're serious about cracking interviews and mastering SQL, you’re in the right place. Let’s grow together and become data experts 🚀 #SQL #DataAnalytics #LearnSQL #DataAnalyst #SQLChallenge #CareerGrowth

You voted. 44% wanted Advanced SQL. So this week — 3 Advanced SQL deep dives, 3 Interview Case Studies, 1 Deep Learning. Following the poll exactly. Day 1: Window Functions. Most data analysts can write GROUP BY. Few can write a window function fluently. That gap is what separates "junior" from "ready for senior" in SQL interviews. The 5 window functions you actually need: → ROW_NUMBER() — assigns 1, 2, 3 within a group (no ties) → RANK() — handles ties with gaps (1, 2, 2, 4) → DENSE_RANK() — handles ties without gaps (1, 2, 2, 3) → LAG() / LEAD() — compare with previous/next row (period-over-period) → SUM() OVER (PARTITION BY ... ORDER BY ... ROWS UNBOUNDED PRECEDING) — running totals The real interview question isn't "what does RANK do." It's "rank customers by total spending within each city, but break ties by signup date." That tests: 1. Did you partition correctly? 2. Did you order correctly? 3. Did you pick the right ranking function? Free notebook covers all 5 with side-by-side examples on a real database: https://lnkd.in/g2hzWJyi Day 1 of 7. Tomorrow: the SQL interview question I've seen at every Tier-1 company. #SQL #WindowFunctions #DataAnalyst #InterviewPrep #AdvancedSQL #DataAnalytics #FreeResources #SQLInterview

🚨 I wish someone gave me this SQL sheet earlier… When I started learning SQL, I was jumping between YouTube videos, random articles, and docs… Result? Confusion + wasted time. Then I found this complete SQL cheat sheet — and it just clicked. It covers everything you actually need 👇 ✔️ Basics → "SELECT", "WHERE", "LIMIT" ✔️ Filtering → "IN", "BETWEEN", "LIKE", "NULL" ✔️ Aggregations → "COUNT", "SUM", "AVG", "GROUP BY", "HAVING" ✔️ Joins → "INNER", "LEFT", "RIGHT", "SELF JOIN" ✔️ Advanced → "CASE", "UNION", Subqueries, and more Basically, all the concepts that show up in Data Analyst interviews — in one place. What I liked the most? No unnecessary theory. Just straight-to-the-point queries you can actually use. Big credit to the original creator for putting this together 🙌 If you’re preparing for Data Analyst / SQL interviews or just want to revise fast… this is a goldmine. Comment “SQL” and I’ll share it with you 👇 #SQL #DataAnalytics #DataAnalyst #LearnSQL #InterviewPreparation #TechCareers #Analytics #CareerGrowth

Day 10 of Learning SQL for Data Analytics 🚀 Most people skip LEFT JOIN… and regret it in interviews. Today I learned one of the most used JOINs in real-world projects 👇 What is LEFT JOIN? ✅ All rows from the LEFT table — always ➕ Matching rows from the RIGHT table ❌ No match? → RIGHT side becomes NULL Real example: 4 employees → only 2 have valid dept_id LEFT JOIN still returns all 4 rows John & Priya get NULL because no department matched Key difference from INNER JOIN: 🔵 INNER JOIN → drops unmatched rows 🟣 LEFT JOIN → keeps ALL left rows, NULLs the rest When to use it? → All customers + their orders (even if no order placed) → All employees + department info (even unassigned) → Finding missing data: WHERE right.col IS NULL 💡 Insight: LEFT JOIN never loses rows from the left table. NULL is not an error — it's information. Day 1 ✅ Day 2 ✅ Day 3 ✅ Day 4 ✅ Day 5 ✅ Day 6 ✅ Day 7 ✅ Day 8 ✅ Day 9 ✅ Day 10 ✅ #SQL #Day10 #DataAnalytics #LearningInPublic #DataAnalyst #SQLJoins #LeftJoin #CareerGrowth

Level Up Your SQL Skills with Real-Time Practice! I’m excited to share a resource I’ve put together: 📘 Real-Time SQL Questions to Practice (Beginner → Advanced) Whether you're starting your journey as a Data Analyst or preparing for interviews, this document is designed to help you: ✅ Strengthen core SQL concepts ✅ Practice real-world scenarios ✅ Improve problem-solving skills ✅ Gain confidence for interviews 💡 Consistent practice is what transforms knowledge into expertise — and SQL is no exception. If you're serious about mastering SQL, this guide can be a great addition to your learning path. Let me know your thoughts or your favorite SQL problem in the comments #SQL #DataAnalytics #DataAnalyst #LearnSQL #SQLPractice #InterviewPreparation #DataEngineering #Analytics #CareerGrowth #TechLearning Magudeswaran | Ajay Babu | Kaviya | Manikanta | Srinivasareddy | Sreethar M B | Suresh | Maureen Direro | Krishnakanth | Gopi Krishna | Satya Sekhar | RAMA | Santosh J. | Mahesh | Sabyasachi | Sainatha | Veeresh | Shafque | Anirban

𝙈𝙤𝙨𝙩 𝙥𝙚𝙤𝙥𝙡𝙚 𝙜𝙚𝙩 𝙘𝙤𝙣𝙛𝙪𝙨𝙚𝙙 𝙗𝙮 𝙎𝙌𝙇 𝙅𝙊𝙄𝙉𝙨. 𝗜𝗡𝗡𝗘𝗥? 𝗟𝗘𝗙𝗧? 𝗥𝗜𝗚𝗛𝗧? 𝗙𝗨𝗟𝗟? 𝗖𝗿𝗼𝘀𝘀? 𝗪𝗵𝗮𝘁 𝗲𝘃𝗲𝗻 𝗶𝘀 𝘁𝗵𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲? I used to feel the same way. But this beginner-friendly PDF makes it crystal clear. Here’s what’s inside ✅ Simple breakdowns of each JOIN ✅ Clear examples to solidify your understanding If you're a → Data Analyst → Data Engineer → Or just someone brushing up on SQL... This is worth saving. I’ve attached the PDF for you here. #SQL #DataEngineering #DevopsLearning #LearningTogether #CareerGrowth

Stop writing basic SQL queries! 🛑 If you want to move from a Junior Analyst to a Senior Data Professional, you have to master the logic that happens beyond the simple WHERE clause. In today’s cheat sheet, I’m breaking down three advanced concepts that separate the pros from the beginners: 🎨 CASE WHEN Mastery: How to pivot data and create custom logic directly in your results. 🛡️ COALESCE vs. ISNULL: Stop letting NULL values break your reports. Know which one to use and when. ⚡ EXISTS vs. IN: The ultimate performance debate. (Hint: One is much better for large datasets!) Master these, and you’ll write cleaner, faster, and more efficient code. 👇 Which of these was the hardest for you to learn? Let’s discuss in the comments! #SQL #DataEngineering #DataAnalytics #SQLTips #Database #CareerGrowth #TechCommunity

😳 I was writing SQL for months… and still getting WRONG results. The problem? I assumed SQL runs top to bottom 👇 SELECT → FROM → WHERE → GROUP BY... But that’s NOT how SQL works 💥 👉 Actual execution order: FROM + JOIN → collect the data WHERE → filter rows GROUP BY → create groups HAVING → filter groups SELECT → pick columns & calculations ORDER BY → sort results LIMIT → restrict output 🔥 Common mistakes almost everyone makes: ❌ WHERE COUNT() > 1 ✅ HAVING COUNT() > 1 ❌ Using column alias in WHERE ✅ Alias works in ORDER BY 💡 Once you understand this, debugging SQL becomes 10x easier. 📌 Lesson: It’s not about how you write SQL… It’s about how SQL executes it. If you're preparing for Data Analyst / Data Engineer roles, this concept is a must know. 👇 Comment “SQL” if you want more interview level tricks! #SQL #DataAnalytics #DataEngineering #LearnSQL #TechCareers #InterviewPrep #DataScience #Analytics #CareerGrowth #LinkedInLearning