#Learn Sql Basics

Confused between INNER JOIN, LEFT JOIN, and RIGHT JOIN? 💻 Here’s the simple logic: INNER JOIN → Only matching rows LEFT JOIN → All left + matching right RIGHT JOIN → All right + matching left Understand the logic once and SQL becomes much easier. Save this reel for revision. #SQL #SQLJoin #LearnSQL #SQLBasics #DataAnalyst

Reverse a Doubly Linked List reverse a doubly linked list step by step. learn how to swap next and prev pointers to reverse the entire list efficiently. important concept for dsa, data structures, and coding interviews. #doublylinkedlist #reverselinkedlist #dsa #datastructures #codingreels

Add Two Numbers in Linked List add two numbers represented by linked lists. learn how to add node by node using carry, just like normal addition. important problem for dsa practice and coding interviews. Hashtags (exactly 5, lowercase): #linkedlist #addtwonumbers #dsa #datastructures #codingreels

Most beginners think SQL is “just coding.” But in simple words? SQL is how you talk to data. You ask: “Show me this.” “Filter this.” “Group this.” “Count this.” And the database replies with answers. That’s it. SQL doesn’t create magic. It helps you find clarity inside messy data. If you understand this, you’ll learn SQL much faster. 🚀 #SQL #DataAnalytics #LearnData #TechCareers

Learn SQL for free! Follow @sundaskhalidd for more content like this ✨ #sql #leetcode #python #dataanalyst

Comment “SQL” to get links! 🚀 Want to learn SQL in a way that actually sticks? This mini roadmap helps you go from complete beginner to writing real queries used in backend, data analytics, and data science. 🎓 SQL Visually Intro Perfect starting point if you are new to databases. You will understand what SQL is, how tables store data, and how queries work using simple visual explanations. Great for building the right mental model before memorizing syntax. 📘 SQL Full Course Now go deep and learn the core SQL you will use everywhere. You will practice SELECT, WHERE, ORDER BY, GROUP BY, HAVING, functions, and filtering patterns that show up in real jobs. This builds strong fundamentals for interviews and projects. 💻 SQL Joins Visual Time to master the most important SQL concept for real world datasets. You will understand INNER JOIN, LEFT JOIN, RIGHT JOIN, and how to think about relationships between tables. This is the skill that makes SQL click for most beginners. 💡 With these SQL resources you will: Understand databases and relational tables clearly Write queries to filter, sort, and summarize data Master joins for real analytics and backend use cases Build portfolio ready projects using SQL and databases If you are serious about data analytics, backend engineering, data engineering, or data science interviews, learning SQL is a must. 📌 Save this post so you do not lose the roadmap. 💬 Comment “SQL” and I will send you all the links. 👉 Follow for more content on SQL, data analytics, and backend fundamentals.

A lot of people are “learning SQL”… but still can’t pass a technical assessment. Why? Because watching ≠ doing. In my cohort, we practice in real time, break things down, and actually understand what we’re doing. That’s the difference. If you’re serious about transitioning into tech, you need more than notes you need application. Follow for real strategies or visit my site to see how to get started #sql #learnsql #techlife #data #datajobs

Comment “sql” for my youtube video on learning SQL in 2026! I used Python in one data job. I used Power BI in another data job. I used SAS in another data job. I used Sisense in another data job. But in ALL data jobs, I’ve used SQL. SQL has been the common denominator of all my data jobs. And it’s absolutely where you should focus 75% of your (tool-based) learning in your career as a data analyst. Because it’s the common thread between MOST data jobs no matter the company and industry. Don’t get distracted by all the millions of fancy tools and all of the new trending courses. Keep it simple, and go for the biggest ROI for your time. SQL is old. It’s tried and true. And it’s not going anywhere anytime soon. Here’s my roadmap to get started learning it ⬇️ Month 1: ↳ basics ↳ sorting ↳ filtering ↳ aggregating / grouping ↳ string manipulation ↳ date manipulation ↳ data cleaning Month 2: ↳ joins ↳ CTEs ↳ Subqueries ↳ set operations ↳ window functions Month 3: ↳ case studies ↳ business application ↳ full projects #sql #dataanalytics #datascience #roadmap 🏷️ data, data analytics, data science, roadmap, sql roadmap, project

Day 26 SQL | COUNT(*) vs COUNT(1) vs COUNT('x') vs COUNT(column) Most SQL learners get this wrong 😳 SAVE this and SHARE with your Data Analyst batch 📊 📺 Follow on YouTube: Link in Bio 👉 www.youtube.com/@DataXOdyssey ❓ Confusion (Looks similar, right?) COUNT(*) COUNT(1) COUNT('x') COUNT(column) COMPLETE QUERY (copy-paste ready): SELECT COUNT(*) AS total_rows FROM employees; SELECT COUNT(1) AS total_rows FROM employees; SELECT COUNT('x') AS total_rows FROM employees; 👉 You can use ANY number or ANY text 👉 Because these values are never NULL ⚠️ 4️⃣ The DIFFERENT one SELECT COUNT(country) AS non_null_countries FROM employees; 👉 Counts ONLY non-NULL values 👉 Rows with NULL are ignored ❌ 🧠 FINAL UNDERSTANDING • COUNT(*), COUNT(1), COUNT('x') → count rows • COUNT(column) → counts non-NULL values only 🎯 Interview Tip: Always use COUNT(*) Use COUNT(column) only when excluding NULLs is intentional 📌 Part of Daily SQL Series – Day 26 🔁 Missed earlier days? Check out previous videos to learn SQL from scratch 🔁 Save this 📌 Follow for daily SQL learning 🔁 DAY SERIES FLOW 👉 Check Out Day 25: LIMIT vs Window Functions #Day26 #DataAnalytics #SQLInterview #LearnSQL #MySQL #PostgreSQL #DataAnalyst #TechJobsIndia #DataXOdyssey #ReelItFeelIt #SQLBeginners #Coding #Programming #DataScience#DataEngineer #TechCareers

Day 29 SQL 🔥 | Tech Company Interview Question SAVE this and SHARE with your Data Analyst batch 📊 📺 Follow on YouTube: Link in Bio 👉 www.youtube.com/@DataXOdyssey 🚫 COMMON DATA ISSUE (VERY IMPORTANT) ❌ Duplicate rows = wrong reports ❌ Double counting users/employees ❌ Poor data quality ✅ SQL helps you identify duplicates instantly 🎯 INTERVIEW TIP (SAVE THIS) 💡 Duplicates are found using GROUP BY + HAVING 💡 Multiple columns are checked together, not separately 💡 This question is asked in almost every tech interview 👉 Interviewers test your data thinking, not just syntax. 🧠 WHAT YOU LEARN IN THIS VIDEO (Beginner Friendly) ✅ 1️⃣ Identify duplicate values SELECT name, department, position_title, COUNT(*) FROM employees GROUP BY name, department, position_title HAVING COUNT(*) > 1; 📌 Groups identical records 📌 Counts how many times they appear 📌 Shows only repeated entries 📌 REAL-WORLD MEANING If the same Name + Department + Role appears more than once, 👉 it’s treated as a duplicate record 🔥 WHY THIS MATTERS • Prevents incorrect reports • Improves data accuracy • Essential for Data Analysts SAVE this for revision 📌 SHARE with your SQL/interview buddy 🤝 Check Out Day 18: WHERE vs HAVING (must-watch) #SQLInterview #LearnSQL #DataAnalyst #TechInterviews #MySQL #DataAnalytics #CodingReels #SQLTutorial #SQLHacks

Most people learn SQL commands… Very few know how to use SQL for real data analysis This SQL for Data Analysis Cheat Sheet covers: ✔ Aggregations ✔ Joins ✔ CASE WHEN logic ✔ Window Functions ✔ Time-based analysis Save this post — you’ll need it for projects, interviews & real jobs Follow for daily SQL & Data Analytics content #SQLForDataAnalysis #DataAnalytics #SQLTips #DataAnalyst #LearnSQL

Want to find totals across categories? That’s where grouping comes in. Whether you’re using SQL, Tableau, or Python, grouping lets you split data into categories and calculate the sum (or any other metric) for each group. Examples: 🍕 Total sales by product 👩‍🎓 Average score by class 🏙️ Revenue by city Once you master this, your analysis instantly becomes more powerful. 👉 Follow for more practical breakdowns like this #datascience #sql #python #tableau #dataanalytics