SQL WHERE vs HAVING: Filtering Data

𝗠𝘆𝗦𝗤𝗟 𝗗𝗮𝘆 𝟲 — 𝗦𝗤𝗟 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀 𝗮𝗻𝗱 𝗖𝗼𝗿𝗲 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 🚀 Today’s session focused on how to effectively work with data using SQL 💻 𝗞𝗲𝘆 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀: • CREATE 🏗️ — define table structure • INSERT ➕ — add records • SELECT 🔍 — retrieve data (no modification) • UPDATE ✏️ — modify existing data • DELETE 🗑️ — remove specific rows • TRUNCATE ⚡ — remove all data quickly • DROP ❌ — delete table completely 𝗖𝗼𝗿𝗲 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀: • WHERE clause 🎯 for precise filtering • AND 🔗 for handling multiple conditions • Arithmetic operations ➕➖✖️➗ in queries • Difference between DELETE, TRUNCATE, DROP ⚖️ • SELECT only retrieves data, it does not alter database values ❗ 𝗦𝗤𝗟 𝗖𝗮𝘁𝗲𝗴𝗼𝗿𝗶𝗲𝘀: DDL | DML | DQL | TCL | DCL 📚 𝗥𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗶𝗻𝘀𝗶𝗴𝗵𝘁: Transactions using COMMIT ✅, ROLLBACK 🔄, and SAVEPOINT 📍 ensure data reliability — just like secure money transfers 💸 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆: SQL is not just syntax — it’s about understanding and controlling data 🧠 #MySQL #SQL #Database #Learning #Tech #FullStack #Day6

Day 2 of my SQL learning journey Solved Find Customer Referee using SQL. Focused on filtering data using conditions and handling NULL values correctly. Key takeaway: Understanding how NULL behaves in SQL is essential when writing accurate queries. #SQL #LeetCode #DataAnalytics #Learning #TechJourney

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 17 of Learning SQL Today I learned about the HAVING clause in SQL and how it helps in filtering grouped data. Here’s what I understood: 🔹 The HAVING clause is used with GROUP BY 🔹 It filters records after aggregation (unlike WHERE) 🔹 Useful when working with functions like COUNT, SUM, AVG 🔹 Helps in analyzing grouped results more effectively 💡 This concept made it clear how to apply conditions on aggregated data, which is very important when working with real-world datasets. Learning SQL step by step is helping me build a strong foundation in data handling and analysis. Every small concept adds up to something powerful! #Day17 #SQL #LearningJourney #DataAnalytics #Programming #Database

🔥 SQL BASICS #1: SELECT + WHERE Mastery Starting my SQL journey with the dynamic duo every data engineer needs! Stop trying to memorize complex queries. Every great data journey starts with mastering the foundational flow: > 1️⃣ **SELECT** - What do you want to see? > 2️⃣ **FROM** - Where is it stored? > 3️⃣ **WHERE** - What are your conditions? > 📌 **SAVE THIS** so you don't lose it! > What SQL topic should I simplify next? > 👇 Let me know in the comments! > #SQL #DataAnalytics #Programming #TechLead #Database

🧠 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

🔹 Difference between LEFT JOIN and RIGHT JOIN in SQL In SQL, JOINs are used to combine data from two or more tables. 👉 LEFT JOIN • Returns all records from the left table • Matching records from the right table • If no match, NULL values are returned for right table columns 👉 RIGHT JOIN • Returns all records from the right table • Matching records from the left table • If no match, NULL values are returned for left table columns 💡 Simple Understanding: • LEFT JOIN → “Give everything from left table” • RIGHT JOIN → “Give everything from right table” 📌 Both joins are useful depending on which table’s data you want to keep fully. #SQL #Database #DataEngineering #Learning #Programming #BackendDevelopment #WebDevelopment #DotNet #InterviewPreparation

Hello everyone! 👋 Welcome to Day 2 of #100DaysOfSQL 🚀 👉 Topic: Types of SQL Commands SQL commands are mainly divided into different categories based on their functionality. 👉 1. DDL (Data Definition Language) Used to define and modify database structure. Examples: - CREATE - ALTER - DROP - TRUNCATE 👉 2. DML (Data Manipulation Language) Used to manage data inside tables. Examples: - INSERT - UPDATE - DELETE 👉 3. DQL (Data Query Language) Used to retrieve data from the database. Example: - SELECT 👉 4. DCL (Data Control Language) Used to control access to data. Examples: - GRANT - REVOKE 👉 5. TCL (Transaction Control Language) Used to manage transactions. Examples: - COMMIT - ROLLBACK - SAVEPOINT 👉 Examples: CREATE TABLE students (id INT, name VARCHAR(50)); INSERT INTO students VALUES (1, 'John'); SELECT * FROM students; 👉 Key Takeaway: Understanding SQL command types helps you organize and write efficient queries. #SQL #LearningJourney #DataAnalytics #100DaysOfSQL

🚀 Understanding SQL Query Execution Order Many developers write SQL queries in the order they appear — but databases don’t execute them that way. Here’s the actual execution flow behind the scenes: 🔹 FROM – Identify the source tables 🔹 JOIN – Combine tables based on conditions 🔹 ON – Apply join conditions 🔹 WHERE – Filter rows before grouping 🔹 GROUP BY – Group rows for aggregation 🔹 HAVING – Filter grouped data 🔹 SELECT – Choose the required columns 🔹 ORDER BY – Sort the result 🔹 LIMIT – Restrict the number of rows returned 💡 Key Insight: Even though we write "SELECT" first, it is executed much later in the process! Understanding this order helps in: ✔ Writing optimized queries ✔ Debugging complex SQL ✔ Improving performance 📌 Master the execution flow, and SQL will start making much more sense. #SQL #Database #BackendDevelopment #DataAnalytics #Programming #Learning