Normalize Data from UNF to 3NF with SQL Tutorial

🚀 Day 2 of My SQL Learning Journey Today I learned about the WHERE clause in SQL. 👉 WHERE is used to filter data based on specific conditions. Basic syntax: SELECT column_name FROM table_name WHERE condition; ✔ Helps in retrieving only the required data ✔ Can be used with operators like =, >, <, AND, OR 💡 Learning WHERE made me realize how powerful SQL is when working with large datasets. Excited to keep improving! 🔥 Next: INSERT statement 👀 #SQL #LearningJourney #Beginner #DataAnalytics #Day2 #LearnInPublic

✅ Solved a SQL problem on StrataScratch — Day 59 of my SQL Journey 💪 Text data looks simple…   until you try to break it into meaningful pieces 👀  Today’s challenge: count how many times each word appears across all rows.  The approach:  • Cleaned and normalised text using LOWER() and REPLACE()   • Used a recursive CTE to split sentences into individual words   • Extracted words step by step using SUBSTRING_INDEX()   • Counted occurrences using GROUP BY  What I practised:  • Recursive CTEs   • String splitting in SQL   • Text normalisation   • Aggregation on derived data  What stood out —  Real-world data isn’t structured.   You often have to create structure first.  Once you break data into the right form,   analysis becomes much easier.  SQL isn’t just about querying tables —   It’s about shaping data into something usable.  Consistent learning, one query at a time 🚀  #SQL #StrataScratch #DataAnalytics #LearningInPublic #SQLPractice

Day by day, I’m building a stronger foundation in SQL. Today’s session was packed with powerful concepts: - Alerts - CTE (Common Table Expressions) - Views - Subqueries - Scalar functions Each topic is helping me think more efficiently when working with data and writing optimized queries. Still learning, still improving. #SQL #DataLearning #Analytics #LearningJourney

#Day_12 of Learning SQL . Today I revisited and strengthened my understanding of: ✔️ INNER JOIN – combining data from related tables ✔️ UNION – merging results from multiple queries -Key Learning: Revisiting concepts with practice helps in building a deeper understanding. INNER JOIN becomes more powerful when applied to real datasets. Focusing on consistency and improving step by step. #SQL #DataAnalytics #LearningJourney #Database #Consistency

Your SQL query can be 100% correct… and still give the wrong answer. Here are 5 common SQL pitfalls I’ve seen (and fixed) in real projects 👇 🚀 What’s a SQL mistake that taught you a big lesson? #SQL #DataEngineering #Analytics #Learning #TechCareers

Quick SQL Refresher! 🚀 If you're working with data, you know that a quick reference guide can save a lot of time. This roadmap breaks down: DDL & DML foundations Joins & Where clauses for filtering Window Functions for advanced analysis Found this useful and wanted to share it with my network. Hope it helps you in your data journey as much as it helped me! #DataAnalyst #SQL #Coding #CareerGrowth #TechTips

SQL Tip of the Day: CASE WHEN THEN Turn raw data into meaningful insights using conditional logic! 💡 Think of it like IF-ELSE in SQL #SQL #DataAnalytics #Learning #InterviewPrep #DataScience #NewtonSchool

📊 SQL Learning Journey Today, I learned a new concept in SQL: HAVING clause So far, I’ve covered: ✔️ SELECT & filtering using WHERE (AND / OR, LIKE) ✔️ ORDER BY for sorting ✔️ GROUP BY for grouping data ✔️ INNER JOIN for combining tables 🔍 Today’s focus: HAVING At first, it felt a bit confusing, but here’s the simple way I understood it: 👉 WHERE filters rows 👉 HAVING filters grouped data 💡 Example: If I group users by plan, HAVING helps me filter only those plans where users are more than a certain number. This small concept made a big difference in understanding how to analyze grouped data more effectively. Step by step, getting more comfortable with SQL. 📈 #SQL #DataAnalytics #LearningJourney #SQLPractice

Learning SQL made me realize something important 👇🏻 Data is useless if you can’t query it properly. Even a simple query like: • SELECT • WHERE • ORDER BY can completely change how you see data. Still practicing, but it's getting interesting 🚀 #SQL #DataAnalytics #Database #LearningSQL

One of the biggest shifts in SQL learning is moving from simple queries to working with multiple tables. Recently focused on JOINs to connect datasets and understand relationships between them, along with UNION to merge query outputs efficiently. This is where SQL starts becoming powerful — not just fetching data, but structuring it in a way that answers real business questions. Continuing to build stronger query logic and analytical thinking step by step. #SQL #DataAnalytics #Learning #DataAnalyst