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Thank you to everyone who joined the FREE SQL EVENT yesterday! If you missed it or want to catch the replay, the full session is now available here: youtu.be/tJ1B1gv_F8Q To keep improving these community events, I’d love your feedback. Please take a moment to fill out this short survey after watching the video: forms.gle/qxixLgUxb8MW5Dyc8 @analystbruh also created a GitHub repository packed with: •Code-along SQL scripts from the session •Extra resources for research •Practice exercises to keep building your skills Check it out here: github.com/analystbruh/sql-s… CALL TO ACTION: 1.Watch the video 2.Explore the GitHub repo 3.Fill out the survey to help shape future events Let’s keep learning and growing together — this is just the beginning! #DataDivaAcademy #SQLTraining #FreeSQLWorkshop #DataCommunity #LearnSQL #DataCareers #BigDataForBeginners

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📜 SQL Cheat Sheet 🔍 Fetching Data (SELECT) SELECT * FROM table_name; SELECT column1, column2 FROM table_name; SELECT DISTINCT column FROM table_name; _____________________________________________________ 🎯 Filtering Data (WHERE) SELECT * FROM users WHERE age > 25; SELECT * FROM orders WHERE status = 'delivered'; _____________________________________________________ 🧩 Multiple Conditions (AND, OR, NOT) SELECT * FROM users WHERE age > 25 AND city = 'Delhi'; SELECT * FROM products WHERE price < 500 OR stock > 50; SELECT * FROM employees WHERE NOT department = 'HR'; _____________________________________________________ 🔢 Sorting Results (ORDER BY) SELECT * FROM employees ORDER BY salary DESC; SELECT * FROM products ORDER BY price ASC, name DESC; _____________________________________________________ 🎛 Limiting & Skipping (LIMIT, OFFSET) SELECT * FROM products LIMIT 5; SELECT * FROM orders LIMIT 10 OFFSET 5; _________________________________________________________ 🏗 Grouping Data (GROUP BY, HAVING) SELECT department, COUNT(*) FROM employees GROUP BY department; SELECT category, AVG(price) FROM products GROUP BY category HAVING AVG(price) > 100; _________________________________________________________ 🏆 Aggregations (COUNT, SUM, AVG, MIN, MAX) SELECT COUNT(*) FROM users; SELECT SUM(price) FROM orders; SELECT AVG(salary) FROM employees; SELECT MIN(age), MAX(age) FROM users; _____________________________________________________ 🔄 Joining Tables (JOIN) 👫 Inner Join SELECT users.name, orders.amount FROM users INNER JOIN orders ON users.id = orders.user_id; _____________________________________________________ 📌 Left Join SELECT users.name, orders.amount FROM users LEFT JOIN orders ON users.id = orders.user_id; _________________________________________________________ 📌 Right Join SELECT users.name, orders.amount FROM users RIGHT JOIN orders ON users.id = orders.user_id; _____________________________________________________ 🔗 Full Join SELECT users.name, orders.amount FROM users FULL JOIN orders ON users.id = orders.user_id; _____________________________________________________ 🏗 Creating & Modifying Tables 🆕 Creating a Table CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100), age INT, city VARCHAR(50) ); _____________________________________________________ 🔧 Altering a Table ALTER TABLE users ADD COLUMN email VARCHAR(100); ALTER TABLE users DROP COLUMN city; _____________________________________________________ 📝 Modifying Data ➕ Inserting Data INSERT INTO users (id, name, age) VALUES (1, 'Amit', 30); _____________________________________________________ 🛠 Updating Data UPDATE users SET age = 31 WHERE id = 1; _____________________________________________________ ❌ Deleting Data DELETE FROM users WHERE id = 1; DELETE FROM users; -- Delete all rows _____________________________________________________ 🏛 Indexes & Keys 🔑 Primary Key CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(100) ); _____________________________________________________ 🔑 Foreign Key CREATE TABLE orders ( id INT PRIMARY KEY, user_id INT, FOREIGN KEY (user_id) REFERENCES users(id) ); _____________________________________________________ 🚀 Creating Index CREATE INDEX idx_name ON users(name); _____________________________________________________ 📜 Subqueries & Unions 🔄 Subquery SELECT name FROM users WHERE id IN (SELECT user_id FROM orders); _____________________________________________________ 🔗 Union (Combine Results) SELECT name FROM customers UNION SELECT name FROM suppliers; SELECT name FROM customers UNION ALL SELECT name FROM suppliers; -- Includes duplicates _____________________________________________________ 🔥 Transactions BEGIN TRANSACTION; UPDATE accounts SET balance = balance - 500 WHERE id = 1; UPDATE accounts SET balance = balance 500 WHERE id = 2; COMMIT; -- Save changes ROLLBACK; -- Undo changes #SQL #SQLTutorial #LearnSQL #SQLQueries #SQLCheatSheet #Database #DataScience #Programming #Tech #Code #SQLForBeginners #SQLBasics #SQLTraining #LearnToCode #CodingForBeginners #AdvancedSQL #SQLPerformance #SQLOptimization #SQLBestPractices #SQLDatabase #MySQL #PostgreSQL #SQLServer #OracleSQL #NoSQL #DataAnalytics #SQLForDataScience #BusinessIntelligence #BigData #DataVisualization

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Day 2: Mastering SQL! Participants explored CRUD operations, joins, and efficient querying to derive real-time data insights. #kssem #kssemai #SQLTraining #DataScience #DataAnalytics #EmpowerWithData

SQL is one of the most valuable skills in data analytics. 𝗟𝗲𝘁'𝘀 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝘀𝗼𝗺𝗲 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 𝘁𝗵𝗮𝘁 𝘆𝗼𝘂 𝘀𝗵𝗼𝘂𝗹𝗱 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝗺𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗮𝘀 𝗮 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘀𝘁 👇 Follow for more! #DataAnalyst #SQLSkills #SQLTechniques #DataAnalytics #SQLMastery #DataAnalysis #DataScience #SQLQuery #DataEngineer #SQLForDataAnalysts #CTE #Subqueries #WindowFunctions #SQLFunctions #BusinessIntelligence #TechSkills #SQLTraining #AnalyticsCommunity #DataDriven #TechCareers #SQLTips #SQLLearning #DataVisualization #DataAnalyticsCommunity #DataProfessionals #AnalyticsJobs #DataCareers #SQLExperts #UKDataAnalytics #USDataAnalytics #EuropeAnalytics #GlobalDataCommunity #HiringDataAnalysts #DataScienceJobs

Here are 4 SQL games to help you learn while playing games at the same time. To avoid getting bored, real quickly, you should try out these SQL games filled with fun and adventure. Have you played any of these? #sqlgames #sqllearning #sqltraining