Mastering SQL Window Functions with DENSE_RANK and SUM() OVER

Day 26/90 — SQL Series | Week 4 "My WHERE clause is not filtering dates correctly." "My SUM is returning NULL instead of a number." 9 times out of 10 — it's a data type mismatch. CAST and CONVERT fix it. CAST('250' AS INT) → turns text into number so you can do math CAST('2024-01-15' AS DATE) → turns text into date so filters work CAST(order_id AS VARCHAR) → turns number into text for concatenation Rule: use CAST (works everywhere). Use CONVERT only when you need date formatting in SQL Server. #SQL #CastConvert #DataAnalytics #LearnSQL #DataAnalyst

Day 33/90 — SQL Series | Phase 2 Subquery in FROM = building a custom table mid-query. "Show only cities with more than 10 orders — sorted by order count." You cannot do this with WHERE alone because WHERE runs before GROUP BY. Solution: group first inside a subquery → then filter the grouped result. SELECT city, order_count FROM ( SELECT city, COUNT(*) AS order_count FROM orders GROUP BY city ) AS city_summary WHERE order_count > 10; The inner query creates a virtual table called city_summary. The outer query reads and filters it like a normal table. Rule: always give the inner query an alias — SQL requires it. CTEs do the exact same thing but cleaner — coming next week. #SQL #Subquery #DataAnalytics #LearnSQL #DataAnalyst

✅ Solved a SQL problem on StrataScratch — Day 54 of my SQL Journey 💪 User activity looks simple… until you try to measure it correctly ⏱️ Today’s problem was about calculating average session time — But sessions weren’t explicitly given. They had to be built from events. The approach: • Identified session boundaries using page_load and page_exit • Used MIN() and MAX() with CASE WHEN to capture valid timestamps • Calculated session duration using TIMESTAMPDIFF() • Filtered out invalid sessions (where load happens after exit) • Averaged session time per user What I practised: • Event-based session reconstruction • Conditional aggregation using CASE WHEN • Time difference calculations in SQL • Data cleaning before aggregation What stood out — Metrics don’t exist in raw data. You have to build them. A “session” isn’t stored anywhere… It’s something you define from behaviour. That’s where analysis actually begins. Consistent learning, one query at a time 🚀 #SQL #StrataScratch #DataAnalytics #LearningInPublic #SQLPractice

SQL Beginner Tip: Write Faster Queries with One Simple Habit One small change can make a noticeable difference, especially with large tables. Stop using SELECT * When you only select the columns you actually need, your queries become faster, cleaner and easier to maintain. I’ve seen this make a real difference when working with large datasets. Reports load faster and dashboards feel smoother. Small habits like this quietly separate average analysts from strong ones. What SQL tip should I share next? #SQL #DataAnalytics #DataAnalyst #SQLTips

#Day-5 #SQL Series – 👉 Today I learned about primary key and foreign key in SQL. Understood how they help in uniquely identifying records and connecting tables. ⭐ primary key:- ✔️ primary key is type of constraint in a table that uniquely identifies each row(a unique id) ✔️ there is only 1primary key and it should be not null 👉Key points:- ⚡Must be unique (no duplicates) ⚡Cannot be NULL ⚡Only one primary key per table ⭐ foreign key:- ✔️ A Foreign Key is a column that links one table to another. 👉 Key points:- ⚡ It refers to a primary key in another table ⚡ Used to maintain relationships between tables ⚡ Can have duplicate values ⚡ Can be NULL (in most cases)  #SQL #Learning #MCA #Consistency

🧠 SQL Table Structure – Simplified If you're starting with SQL, understanding this is a game changer 👇 📌 Table → Organized data in rows & columns 📌 Column → Defines data type (Name, Email, etc.) 📌 Row → One complete record 🔑 Primary Key Unique ID for each row (no duplicates, no NULLs) 🔗 Foreign Key Connects tables → builds relationships between data 💡 Think of SQL like a well-structured system where relationships matter more than just data. Master this foundation, and everything else becomes easier. #SQL #Database #PowerBI #Codebasics #DataLearning #TechBasics

Day 15 of my SQL series Today I covered window functions using ROW_NUMBER. This allows us to rank data without grouping it — a very powerful concept in SQL. Next: RANK & DENSE_RANK #SQL #DataAnalytics #Learning #CareerGrowth

We’ve officially entered the Intermediate SQL Series 🚀 Starting strong with JOINS — one of the most important SQL skills. Watch here 👇 https://lnkd.in/djRu4BbR

🔰 PHASE–2 | CORE SQL QUERIES SELECT Statement – The Foundation of Data Retrieval The SELECT statement is the backbone of SQL. Every meaningful interaction with a database begins here. In this phase, I focused on: 📌 Basic SELECT syntax – understanding query structure 📌 Selecting specific columns – retrieving only relevant data 📌 Readable & efficient queries – clarity matters in real projects Mastering SELECT is not just about fetching data — it’s about asking the right questions from the database. This forms the base for advanced concepts like filtering, aggregation, and analytics used in: 💼 Backend Development 📊 Data Analysis 🗄 Database-driven Applications Step by step, strengthening my SQL fundamentals — one query at a time. 🚀 #SQL #DatabaseFundamentals #BackendDevelopment #DataSkills #LearningInPublic #TechCareers #SoftwareEngineering #SQLQueries #CareerGrowth