Marian Egharevba’s Post

I used to overuse subqueries in SQL. It worked… but it made my queries harder to read and sometimes slower. Then I started using CTEs (Common Table Expressions). And everything became much cleaner. Instead of this: SELECT * FROM ( SELECT CustomerID, COUNT(*) AS TotalOrders FROM Orders GROUP BY CustomerID ) t WHERE TotalOrders > 5 You can write: WITH OrderSummary AS ( SELECT CustomerID, COUNT(*) AS TotalOrders FROM Orders GROUP BY CustomerID ) SELECT * FROM OrderSummary WHERE TotalOrders > 5 Same result — but much easier to read and maintain. Lesson I learned: Readable queries are easier to debug, optimize, and scale. Do you prefer subqueries or CTEs in your work? #SQL #SQLServer #DataEngineering #DatabaseDeveloper #TechTips

Mini SQL Lesson I have learned so far Why does my command window say “Disconnected”? So this happened to me I opened my SQL ready to continue practicing, only to see “Disconnected” 😩 At first, I thought I had done something wrong. It simply means your SQL is no longer connected to the server so it can’t run your commands. To fix this: Just reconnect to your server (like localhost or SQLEXPRESS) and you are good to go. What I have learned is that not every error means you are stuck sometimes, it’s just a small fix. Learning SQL one step at a time and I am loving the process. TechCrush @ Techcrush.pro #RisewithTechCrush #Tech4Africans #LearningwithTechCrush

🔥 Magic Tables in SQL Server – They Appear Magically! 🔥 You don’t create them. You don’t code them. Yet… they exist in the background every time you run INSERT, UPDATE, or DELETE. These are called Magic Tables (also known as Inserted & Deleted virtual tables). Here’s exactly how they work: ✅ INSERT → New row instantly appears in the INSERTED magic table. ✅ DELETE → Deleted row goes into the DELETED magic table. ✅ UPDATE → Old (previous) row → DELETED table                 New (updated) row → INSERTED table They are temporary logical tables maintained automatically by SQL Server. What's the main usage? It's used mainly inside TRIGGERS (these can be very good for auditing and validation, or for implementing complicated business logic). DBAs love magic tables, and all developers should be familiar with them. Have you ever implemented a magic table in your trigger? Let me know in the comments below 👇. #SQLServer #SQL #Database #Triggers #MagicTables #Backend #DataEngineering #TechTips #LinkedInLearning #CareerGrowth #DevelopersOfLinkedIn #TechCommunity #ITJobs #SoftwareDeveloper #EngineeringLife #TechTips #DailyLearning #CodeNewbie #DeveloperCommunity #LearnToCode #CodingLife #TechCareer #Upskill #KnowledgeSharing #MagicTables #SQLTriggers #DatabaseTriggers #SQLTips #SQLTutorial #LearnSQL #DatabaseConcepts #SQLDeveloper #DataManagement

#Day_24 of learning SQL in 60 days Topic I covered: CONCAT () Function Today I learned about the CONCAT () function in SQL, which is used to combine two or more strings into a single string. Syntax: CONCAT (string1, string2, ..., stringN) Example: SELECT CONCAT ('Hello', ' ', 'World') AS Result; Output: Hello World Using CONCAT () with Table Data: SELECT CONCAT (emp_name, ' - ', emp_email) AS Employee_Details FROM employees; This helps in combining multiple columns into a single readable format. Real-Time Use Cases: ✔️ Creating full names (First Name + Last Name) ✔️ Formatting output for reports ✔️ Generating custom messages ✔️ Combining columns for better readability Note: If any value inside CONCAT () is NULL, the result will also be NULL (in MySQL). Learning SQL step by step and exploring how small functions can make a big difference! #SQL #MySQL #Learning #DataAnalytics #Database #TechSkills  

Day 26 & 27 – SQL Learning Journey Subqueries — a concept that looks difficult at first but becomes very straightforward once you understand the logic behind it. A subquery is simply a query inside another query. Instead of solving everything in one complex statement, you break the problem into smaller steps and let SQL handle it cleanly. Here are the core types I learned: • Single-row subquery Returns one value and is used with operators like =, <, > • Multiple-row subquery Returns multiple values and works with IN, ANY, ALL • Correlated subquery Runs for each row of the outer query and depends on it What I realized : The problem is not subqueries — it’s how we approach them. Once the thinking is clear, they become one of the most useful tools in SQL. 1) Independent (non-correlated) → runs once 2) Dependent (correlated) → runs per row “Only correlated subqueries depend on the outer query.” They help simplify logic, improve readability, and handle real-world use cases more effectively. #SQL #LearningJourney #DataAnalytics #SQLDeveloper #TechSkills

🚀 Day 7 | SQL Learning Journey — Mastering SQL Operators ⚡ Today I went deep into SQL Operators — the real building blocks behind writing precise and efficient queries. Operators may look simple, but they control how data is filtered, compared, and manipulated inside the database. Here’s what I explored today 👇 🔹 Arithmetic Operators +, -, *, /, % Used for performing calculations directly in queries 🔹 Comparison Operators =, !=, >, <, >=, <= Helped in comparing values and filtering specific records 🔹 Logical Operators AND, OR, NOT Combined multiple conditions to make queries smarter 🔹 Special Operators BETWEEN – filtering within a range IN – matching multiple values LIKE – pattern-based searching IS NULL – handling missing values 🔹 Bitwise & Compound Operators (basics) #sql #queries #mysql #structured #query #language

I’m learning that SQL errors are often not about “complex code” but about small things: query order, punctuation, capitalization, and spelling. What appears to be a logic problem is a missing comma, incorrect keyword placement, or a filter written in the wrong way. The more I practice, the more I see that understanding how SQL thinks makes debugging much easier. Two lessons stood out for me: first, SQL needs structure in the right order, especially knowing where the data is coming from before applying selections and filters. Second, filtering becomes much more powerful when you understand operators like AND, OR, BETWEEN, IN, LIKE, IS NULL, and IS NOT NULL. My biggest takeaway: when debugging SQL, start by checking syntax and query flow first, then review your filtering logic step by step. #SQL #learninginpublic #data

NULL in SQL is not zero. It's not an empty string. It means "unknown." This confuses almost every beginner — including me when I started. ❌ This won't work: WHERE email = NULL ✅ This is correct: WHERE email IS NULL Because NULL isn't a value to compare — it's an absence of value. Also useful: → IS NOT NULL — find rows that DO have a value → ISNULL(column, 'default') — replace NULLs with something useful Handling NULLs properly prevents silent bugs in your queries. Did NULL confuse you when you first learned SQL? 😄 #SQL #SQLTips #DataCleaning #TechTips #LearnSQL

✅ SQL doesn’t allow duplicate objects ✅ Always check before creating database/table ✅ Use safe queries like: IF DB_ID(‘schooldb’) IS NULL CREATE DATABASE schooldb; IF OBJECT_ID(‘students’) IS NULL CREATE TABLE students (…); ⸻ 💭 Lesson of the day: “Not all errors mean your logic is wrong — sometimes it’s just repetition.” ⸻ 🔥 If you’re learning SQL: Don’t just memorize queries… Understand why errors happen. #SQL #Learning #Beginners #DataAnalytics #CareerGrowth #LinkedInLearning #TechJourney

💡SQL WHERE Clause Learning Today I spent some time revisiting one of the most basic yet powerful SQL concepts — WHERE clause. It looks simple, but in real production scenarios it makes a huge difference. Without WHERE → huge data retrieval With WHERE → precise and faster results While practicing queries, I realized that writing efficient filters helps reduce load on the database and improves performance. Sometimes the smallest SQL concepts create the biggest impact in real-time applications. Staying consistent with daily SQL practice and learning step by step. 💻 #SQL #Database #SQLLearning #ApplicationSupport #opentonewjobs