SQL Joins, GROUP BY & HAVING with SQL Queries

Understanding the difference between WHERE and HAVING is key to writing efficient SQL queries—filter early, aggregate smartly, and analyze better. #DataAnalytics #SQL #BusinessIntelligence #DataAnalyst #AnalyticsLearning #DataScience #SQLQueries

i thought SQL queries execute step by step but but that’s not how it actually works SQL doesn’t start with SELECT it starts with FROM here is the logical order SQL processes a query : 👇 1️⃣ SQL gets the data (FROM) 2️⃣ combines tables if needed (JOIN/ON) 3️⃣ filters rows (WHERE) 4️⃣ groups data (GROUP BY) 5️⃣ filters groups (HAVING) 6️⃣ selects columns (SELECT) 7️⃣ removes duplicates (DISTINCT) 8️⃣ sorts results (ORDER BY) 9️⃣ limits the output (LIMIT) once I understood this, writing queries felt a lot easier 😁 #dataanalyst #dataanalytics #sql #learninginpublic

DAY 46 — Lessons Learned Using SQL in Real Projects After working with SQL across multiple datasets, here are key lessons: 1️⃣ Always start with the business question 2️⃣ Keep queries simple and readable 3️⃣ Validate results at every step 4️⃣ Understand your joins deeply 5️⃣ Document your logic SQL is not just a technical skill. It is a thinking process. The goal is not to write complex queries. It is to produce reliable, meaningful insights. #ShinaAwopejuBusinessAnalysisJourneyWith10alytics #BusinessAnalysisWith10alytics #DataAnalysis #SQL

🌳 SQL Practice Series | Problem # 1 Binary Search Tree Node Classification I've been doing consistent SQL practice lately as part of my data analytics journey, and this one made me think. The challenge: given a BST table with nodes (N) and their parents (P), classify every node as Root, Inner, or Leaf using pure SQL. The logic breaks down simply: → Root: P is NULL no one is above it → Leaf: no other node lists it as a parent → Inner: has both a parent and children My Solution: NOT EXISTS with a correlated subquery checks whether any row references the current node as a parent. If none do it's a Leaf. Clean, readable, and it works on any size tree. How would you solve this differently? Would you go with a JOIN, a subquery, or something else entirely? Drop your approach in the comments I'd love to see different ways to think about it! #SQL#SQLPractice#DataAnalytics#HackerRank#LeetCode#DataEngineering#TechInterview#100DaysOfCode#MTSU

SQL JOIN'S 📌 While learning SQL, one thing became clear to me — data is usually not stored in one place. It’s divided into multiple tables, and that’s where JOIN becomes important. So, what is SQL JOIN? SQL JOIN is used to combine data from different tables using a common column, so we can see the complete picture. Simple example: We have: Customers table (Customer_ID, Name) Orders table (Customer_ID, Order_Amount) Using JOIN, we can connect both tables and understand: which customer made which purchase Types of JOIN: INNER JOIN– gives only matching data from both tables, LEFT JOIN– gives all data from left table + matching from right, RIGHT JOIN – gives all data from right table + matching from left, FULL JOIN– gives all data from both tables, What I understood: JOIN is not just about writing queries… it’s about connecting data to understand what’s actually happening. #SQL #DataAnalytics #LearningJourney #BusinessAnalytics #DataScience

🚀 Day 33 – Top 50 SQL Questions Today’s problem: Consecutive Numbers 🔍 Objective: Find numbers that appear at least three times consecutively in a dataset. 💡 Approach: Used self joins on the Logs table Matched rows based on consecutive id values Compared num values across three rows Applied DISTINCT to ensure unique results 🛠️ SQL Query: SELECT DISTINCT l1.num AS ConsecutiveNums FROM Logs l1 JOIN Logs l2 ON l1.id = l2.id - 1 JOIN Logs l3 ON l1.id = l3.id - 2 WHERE l1.num = l2.num AND l2.num = l3.num; 📈 Key Insight: Self joins are highly effective for identifying sequential patterns in relational data. #SQL #DataAnalytics #LeetCode #ProblemSolving #Day33

📊 Day 13 – SQL JOINS (Introduction) SQL JOIN is used to combine data from multiple tables. It helps in: ✔ Connecting related data ✔ Fetching meaningful information ✔ Performing deeper analysis 💡 Example: A company has: - Customer Table - Orders Table Using JOIN, we can find: 👉 Which customer placed which order Learning JOINs helps in working with real-world databases. Excited to explore more SQL concepts 🚀 #SQL #DataAnalytics #SQLJoins #Day13 #LearningInPublic

📊 Day 12 – Basic SQL Queries SQL is used to interact with databases and retrieve specific data. Today I explored some basic SQL queries: ✔ SELECT → To retrieve data ✔ WHERE → To filter data ✔ ORDER BY → To sort data 💡 Example: Find top-selling products using: SELECT * FROM sales WHERE revenue > 1000 ORDER BY revenue DESC; These basic queries are the foundation for working with real-world datasets. Excited to learn more advanced queries 🚀 #SQL #DataAnalytics #Day12 #LearningInPublic

Day 18 of my SQL learning journey has been insightful as I explored the CASE Statement. I applied IF-THEN logic in SQL, categorized data using conditions, and created dynamic columns. A key takeaway from today is the importance of transforming data using logic, not just queries. SQL continues to grow in power every day. #SQL #LearningJourney #Day18 #DataAnalytics #TechSkills

Day 28 SQL Learning Journey I explored the INSERT INTO SELECT statement in SQL and it’s a powerful way to move data between tables efficiently. In simple terms, it allows you to copy data from one existing table and insert it into another existing table, all within a single query. How it works: You select data from a source table Then insert it directly into a target table Key things to remember: The column structure must match (same number of columns and compatible data types) It adds new rows to the target table without affecting the existing data Why this is useful: 1. Backing up specific records 2. Migrating data between tables 3. Saving time when working with large datasets #SQL #Data Analyics #NightStudy #LearningJourney #DataSkills #TechGrowth