Stages of running a SQL query: Stage 1: Write the query confidently Stage 2: Hit Run Stage 3: "0 rows returned" Stage 4: Stare at the query for 10 minutes Stage 5: Add a WHERE 1=1 for no reason Stage 6: Realize you spelled the column name wrong Stage 7: It works. Pretend it was always going to work. Tell me your Stage 6 moment in the comments. #SQL #DataAnalyst #DataHumor #CodingMemes #ProgrammerHumor #TechHumor #DataAnalytics #SQLMemes
Spelling SQL column name wrong, then it works
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You can learn all of this in weeks. Knowing SQL ≠ Being job ready Can you write queries without guidance? Can you debug when it breaks? That’s the real test.
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“Here is some basic SQL notes… saved for future me (and anyone else who needs it).” Because let’s be honest — we all learn SQL… and then forget the syntax the moment we actually need it 😅 So instead of pretending I’ll remember everything, I decided to document the basics: - Core queries - Filtering - Aggregations - Joins & more Nothing fancy. Just the stuff that actually gets used. Sometimes the smartest thing in tech isn’t knowing everything… it’s knowing where you saved it 😉 #SQL #DataAnalytics #DataScience #LearningInPublic #TechNotes
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🗓️ SQL Challenge Day #27: Biggest Single Number 🔹 Find the largest number that appears exactly once! 🔢 🔹 Problem: Return the biggest "single" number (appears only once): ✅ If no such number exists, return NULL 🔹 Solution: SELECT MAX(num) AS num FROM ( SELECT num, COUNT(1) AS cnt FROM MyNumbers GROUP BY num HAVING cnt = 1 ) t; ✅ Result: Accepted 💡 Key Takeaway: **MAX() handles NULL gracefully!** The outer query returns NULL automatically if the inner subquery finds no single numbers – no extra logic needed. This is cleaner than using CASE or IFNULL here. 👇 Your turn: What’s your go-to pattern for handling "return NULL if empty result" scenarios in SQL? #SQL #LeetCode #DataEngineering #ProblemSolving #Coding #LearningInPublic #Database #DataAnalytics
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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
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🚀 EXISTS in SQL 💡 What is EXISTS? ✔️ Check if a subquery returns any rows ✔️ Returns TRUE if at least 1 row exists ✔️ Returns FALSE if no rows 🔍 How it works: ➡️ Outer query runs ➡️ Inner query checks for matching rows ➡️ If a match is found, the row is included ➡️ If no match, the row is excluded 🗝️ Key Concept 👉 EXISTS does not care about values 👉 It only checks if rows exist 🧠 Even if the subquery returns NULL ➡️ EXISTS can still be TRUE #SQL #DataAnalytics #LearningSQL #TechTips #InterviewPrep #DataEngineering
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Day 18 of my SQL learning journey has been insightful as I explored the CASE Statement. I applied IF-THEN logic in SQL, categorized data using conditions, and created dynamic columns. A key takeaway from today is the importance of transforming data using logic, not just queries. SQL continues to grow in power every day. #SQL #LearningJourney #Day18 #DataAnalytics #TechSkills
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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
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🗓️ SQL Challenge Day #32: Consecutive Numbers 🔹 Find numbers appearing 3+ times in a row! 🔢 🔹 Problem: Identify values with ≥3 consecutive occurrences: ✅ Consecutive = sequential `id` values ✅ Return distinct numbers only 🔹 Solution (Window Function Approach): SELECT distinct num AS ConsecutiveNums FROM ( SELECT num, id, LEAD(id) OVER (PARTITION BY num ORDER BY id) AS l1, LEAD(id, 2) OVER (PARTITION BY num ORDER BY id) AS l2 FROM Logs ) t WHERE l1 - id = 1 AND l2 - l1 = 1; ✅ Result: Accepted 💡 Key Takeaway: **LEAD() checks sequence gaps!** By comparing current `id` with next two `id`s: - `l1 - id = 1` → next record is immediate successor - `l2 - l1 = 1` → third record is also consecutive ⚠️ Why partition by `num`? Ensures we only compare same numbers! 👇 Your turn: Have you used LAG/LEAD for detecting sequences in logs or time-series data? What patterns did you find? #SQL #LeetCode #DataEngineering #ProblemSolving #Coding #LearningInPublic #Database #DataAnalytics
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Day 15 of My DSA Journey - SQL Shifted focus to SQL today and worked on multiple problems from the SQL study plan on LeetCode What I learned: • How to retrieve and filter data using SELECT • Using JOINs to combine multiple tables • Applying GROUP BY and aggregate functions • Writing clean and structured queries Progress so far: • 23 out of 50 SQL problems completed Insight: SQL problems are less about syntax and more about understanding the data and relationships between tables. Once the logic is clear, writing the query becomes straightforward. #DSA #SQL #ProblemSolving #LearningJourney #Database
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