Understanding the HAVING Clause in SQL

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 6 of learning SQL 🚀 Today I learned one of the most important concepts in SQL: JOIN. I finally understood how to combine data from multiple tables and why it’s essential for real-world data analysis. Topics I covered: ✔ INNER JOIN – returns only matching data from both tables ✔ LEFT JOIN – returns all records from the left table, unmatched values as NULL ✔ RIGHT JOIN – returns all records from the right table ✔ Self JOIN – joining a table with itself for advanced comparisons Example I practiced: SELECT e.name, d.department FROM employees e LEFT JOIN departments d ON e.dept_id = d.dept_id; Key learning today 💡 JOIN connects data across tables using a common key The ON condition is the most critical part of a JOIN LEFT JOIN is very useful when you don’t want to lose any data This concept really changed how I think about databases. Goal: Become job-ready in SQL & Data Analysis 💪 #SQL #DataAnalytics #LearningInPublic #100DaysOfCode #Consistency #Alextheanalyst

#Day_20 of learning SQL in 60 days Topic I covered: SQL Learning: GROUP BY with Multiple Columns Today I explored how the GROUP BY clause can be used with multiple columns in SQL — a powerful way to organize and analyze data Normally, GROUP BY is used to group rows based on a single column. But when we use multiple columns, SQL groups data based on the unique combination of those columns. 🔹 Syntax: SELECT column1, column2, AGGREGATE_function(column3) FROM table_name GROUP BY column1, column2; 🔹 Example: SELECT dept_id, subject, COUNT(*) AS total_staff FROM staff GROUP BY dept_id, subject; This query groups STAFF on the columns dept_id and subject. 🔹 Key Points: ✔️ Groups are formed using combinations of multiple columns ✔️ All selected columns must be either in GROUP BY or used with aggregate functions ✔️ Helps in detailed data analysis and reporting 🚀 Learning how to use GROUP BY with multiple columns really improves how we analyze structured data in SQL! #SQL #Database #DataAnalytics #Learning #GroupBy #SQLBasics  

#Day_10 of Learning SQL . Today I explored important concepts in SQL and learned: ✔️ HAVING clause – used to filter grouped data after applying GROUP BY ✔️ Primary Key – uniquely identifies each record in a table (no duplicates, no NULL values) ✔️ Foreign Key – creates a relationship between two tables and maintains data integrity 💡 Key Learning: WHERE is used to filter rows before grouping, while HAVING is applied after grouping. Primary and Foreign Keys help in organizing relational databases and ensuring consistency across tables. Gaining a deeper understanding of how structured data is connected and managed . #SQL #DataAnalytics #LearningJourney #Database #Consistency

🚀 Day 9 of My SQL Learning Journey — Understanding the HAVING Clause 📊 Today I learned a small SQL concept that makes a big difference in real-world data analysis — HAVING. Most people stop at WHERE. But real insights start after grouping data. 🔹 WHERE filters rows 🔹 HAVING filters grouped results 👉 That means HAVING helps answer questions like: ✔ Which departments have more employees? ✔ Which customers appear multiple times? ✔ Which groups cross a certain threshold? 💡 Key Realisation: Data analysis isn’t just about retrieving rows — it’s about filtering meaningful summaries. Learning SQL this way is changing how I think about data, not just how I write queries. 📈 One concept at a time. Done right. On to Day 10… 🚀 #SQL #DataAnalytics #LearningInPublic #MySQL #HAVING #Consistency #CareerGrowth #Placements #CSE

How do you know if your SQL query is actually correct? I've been learning SQL daily and writing a few queries each day. Something I'm starting to realize is that just because a query runs and gives results doesn’t mean it’s right. There have been times when I wrote a query, saw clean numbers, and felt confident. However, upon closer inspection, I found small mistakes, wrong joins, missing conditions, or assumptions I didn’t question. Now, I'm trying to slow down a bit. I aim to not just write queries but to understand them fully. I check the logic, validate the output, and ask myself: does this actually make sense? It's a small shift, but I can already see the difference. I'm still learning, one query at a time. For those who’ve been through this, what helped you get better at SQL ? #data #SQL #DataAnalytics #AnalyticsTips #LearnSQL

💡 SQL made SIMPLE! When I started learning SQL, everything felt confusing — Joins, DDL, DML, Functions… 🤯 But once I visualized it like this, everything started making sense. 📊 This SQL Mindmap covers: ✔ DDL, DML, DCL ✔ Joins & Functions ✔ Group By, Where, Order By ✔ Window Functions If you're a beginner or preparing for Data Analyst roles, this is a must-save! 🚀 Consistency + Practice = SQL mastery 💪 📌 Save this for later 🔁 Share with someone learning SQL #SQL #DataAnalytics #DataAnalyst #Learning #CareerGrowth #TechSkills #Beginners #AnalyticsJourney

Understanding SQL is becoming more important as data becomes more crucial in every industry. That's why I took the SQL Introduction Short Class on MySkill. What surprised me was that SQL actually shares the same principle as Excel. So I just need to adapt to the commands and the system, and it clicked pretty fast from there. I really enjoyed learning this tool and honestly, I hope to learn more! What I explored in this class: - How databases work and what SQL's role is in a DBMS - SQL functions: DDL, DQL, and DML - Data types: Character, Numeric, and Temporal - A real case study analyzing retail sales data using SQLite Online And with this foundation, I now understand how to query, filter, and pull data to support better decision making, which turns out to be relevant way beyond just "data roles." Still in the early stage, but I'm genuinely excited to keep going. 🚀 #SQL #DataAnalysis #MySkill #Learnatmyskill

SQL can feel overwhelming at first, but it’s one of the most essential tools for any Data Analyst. Here are the core concepts I focus on: • joins and filtering • aggregations and grouping • window functions Mastering these allows you to work with real datasets and extract meaningful insights. SQL is not just a skill — it’s a foundation for data-driven decision-making. It covers: DDL, DML, DCL basics Joins and filters Functions and window functions Core concepts you’ll use every day 👉 Save it for later 👉 Use it while learning 👉 Share it with someone who’s just starting #SQL #DataAnalytics #DataBasics #DataCommunity

#Day_31 of learning SQL in 60 days Topic I covered: SQL Concept I Learned: LEFT JOIN Today I explored LEFT JOIN in SQL, and it really helped me understand how to work with incomplete or missing data. A LEFT JOIN in SQL is used to retrieve all records from the left table and the matching records from the right table. If there is no match, the result will still include the left table’s row, but the right table’s columns will contain NULL values. Syntax: SELECT COLUMN_NAME(S) FROM TABLE1 LEFT JOIN TABLE2 ON TABLE1.COMMON_COLUMN=TABLE2.COMMON_COLUMN; A LEFT JOIN returns: ✔️ All records from the left table ✔️ Matching records from the right table ✔️ NULL values if there is no match Example: SELECT STAFF.EMP_NAME, DEPARTMENTS.DEPT_NAME FROM STAFF LEFT JOIN DEPARTMENTS ON STAFF.DEPT_ID=DEPARTMENTS.DEPT_ID; This query shows all EMPLOYEE NAMES along with their department names. If the EMPLOYEE is not assigned to any department, the department column will show NULL. Use Cases: 🔹 Finding missing or unmatched data 🔹 Displaying complete lists with optional details 🔹 Data analysis where not all records have relationships Learning SQL step by step and building a strong foundation in joins! #SQL #Database #Learning #Tech #DataAnalytics