Mastering SQL with JOINs and UNION for Data Analytics

Today I strengthened my foundation in SQL by learning some core concepts and commands. I explored: • SQL basics and its importance in managing data • DDL (Data Definition Language) – CREATE, ALTER, DELETE • DML (Data Manipulation Language) – working with data inside tables • DQL (Data Query Language) – retrieving data using SELECT • Creating and modifying tables using CREATE TABLE and ALTER Understanding these concepts helped me see how databases are structured and how data is stored, updated, and retrieved efficiently. Step by step, I’m building my skills in SQL and data handling. #SQL #DataAnalytics #LearningJourney #Database #TechSkills #DataLearning

#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

🚀 Strengthening my SQL skills! Recently, I’ve been revisiting some intermediate SQL concepts that are extremely useful in real-world data scenarios: ✔️ Window Functions (RANK, LAG, Running Totals) ✔️ CTEs (Common Table Expressions) for better readability ✔️ Subqueries (including correlated subqueries) These concepts help in writing efficient, optimized, and readable queries, especially when working with large datasets. Sharing a quick cheatsheet for anyone looking to brush up their SQL skills 👇 #SQL #DataAnalytics #Snowflake #Learning #DataEngineering #WomenInTech

I used to and still sometimes do jump straight into writing SQL queries. Open the dataset → start querying. But recently, I’ve been trying a different approach. Now I pause and ask: → What exactly am I trying to find? → What does each column actually represent? → What kind of result would make sense? Because writing queries is easy. Understanding the data is not. That small shift is slowly changing how I approach problems. Still learning, but it already feels more structured. Do you also take time to understand the data first, or jump into queries? 👇 #DataAnalytics #SQL #Learning #DataThinking

I used to think SQL was just theory… until I actually used it 😳 🚀 Day 3 of my Data Analytics Journey Today I learned the basics of SQL: • SELECT – to fetch data • WHERE – to filter data • ORDER BY – to sort results But here’s what changed everything 👇 👉 I stopped memorizing queries 👉 I started practicing on real datasets And suddenly… SQL started making sense. 💡 Biggest learning: SQL is not about syntax, it’s about thinking logically with data. Tomorrow I’ll learn JOINS (the most important part 🔥) 💬 What was the toughest SQL topic for you? #SQL #DataAnalytics #LearningInPublic #BeginnerJourney #Tech

✅ 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 55/90 — SQL Learning: Combining Data (JOINs Introduction) Today I started learning one of the most important concepts in SQL: 👉 JOINs Real-world data is usually stored in multiple tables… and JOINs help us connect them 🔗 Here’s what I learned: ✅ What is a JOIN? (combining tables) ✅ Understanding common columns (keys) ✅ Introduction to different JOIN types - INNER JOIN - LEFT JOIN - RIGHT JOIN Example: 👉 Combine customer data + orders data 👉 Get meaningful insights from multiple tables 💡 Big lesson: Single table = Limited information Multiple tables + JOIN = Real insights 📊 Because: Disconnected data → Incomplete ❌ Connected data → Powerful analysis ✅ From today, I’m stepping into real-world SQL concepts 🚀 💬 Have you tried JOINs in SQL yet? #SQL #DataAnalytics #LearningInPublic #DataAnalystJourney #90DaysChallenge

📊 Day 56/90 — SQL Learning: INNER JOIN (Deep Dive) Today I explored the most commonly used JOIN: 👉 INNER JOIN This is where SQL starts feeling like real-world problem solving 🔥 Here’s what I learned: ✅ INNER JOIN returns only matching records ✅ It connects tables based on a common column (key) ✅ Non-matching data is excluded ✅ Most used JOIN in real-world queries Example: 👉 Get customers who placed orders 👉 Combine customer + order details 💡 Big lesson: INNER JOIN focuses on common data between tables Because: No match → Ignored ❌ Match → Included ✅ Example Query: SELECT c.name, o.amount FROM customers c INNER JOIN orders o ON c.id = o.customer_id; From today, I’m understanding how real datasets are connected 🔗 💬 Where do you use INNER JOIN in real projects? #SQL #DataAnalytics #LearningInPublic #DataAnalystJourney #90DaysChallenge

Most people learn SQL by memorizing queries… but the real power comes from how you control the data you extract. That’s where logical operators come in. Using AND, OR, NOT, and IN completely changes how your query behaves: → AND narrows down results (strict filtering) → OR expands possibilities → NOT removes unwanted data → IN simplifies multiple conditions Same dataset, different logic → completely different insights. While learning SQL for data science, I realized that writing a query is easy… but writing the right query is what actually matters. #SQL #DataScience #LearningSQL #DataAnalytics #SQLQueries #MySQL #DataAnalysis #TechLearning #DataSkills #AnalyticsJourney