SQL LeetCode Challenge: Identifying Study Spirals with ROW_NUMBER() and LAG()

✅ Solved a SQL problem on LeetCode — Day 43 of my SQL Journey 💪 Text looks simple… until you try to handle every edge case ✍️ Today’s problem was about transforming text — capitalising the first letter of each word, while handling special cases like hyphens correctly. I used recursive logic and string operations to: • Break text into individual characters using recursive CTE • Track previous characters using window functions • Identify word boundaries and special cases • Apply conditional uppercase/lowercase transformations • Reconstruct the final string using GROUP_CONCAT What I practised: • Recursive CTEs for step-by-step processing • Using LAG() to track character-level context • Writing precise CASE conditions for formatting • Handling edge cases like hyphenated words What stood out — Text transformations aren’t just formatting… they’re about handling context. A single character can change the logic, and missing one condition can break everything. That’s where attention to detail matters most. SQL isn’t just for numbers and aggregations. It can handle complex text logic too. Consistent learning, one query at a time 🚀 #SQL #LeetCode #SQLPractice #DataAnalytics #LearningInPublic

📝 Deep Dive into SQL Fundamentals. Data is only as good as the way you manage it. I’ve been documenting the core principles of Structure Query Language (SQL)—from basic syntax to advanced database relationships. My latest notes cover: 🔹 CURD Operations (Create, Update, READ, Drop). 🔹 Relational Keys (Primary vs. Foreign). 🔹 Logical Operators for precise data retrieval. Always learning, always growing. 📈 #SoftwareEngineering #SQL #Database #Programming #Notes #LearningJourney

✅ Solved a SQL problem on LeetCode — Day 41 of my SQL Journey 💪 Learning isn’t random… it follows patterns you can actually track 📊 Today’s problem was about identifying the most common course transitions among top-performing students — what high achievers tend to study next. The approach: • Filtered top performers based on course count and average rating • Used LEAD() to find the next course in each user’s sequence • Paired consecutive courses to map learning paths • Counted how often each transition appeared What I practised: • Window functions for sequence analysis • Using PARTITION BY for per-user ordering • Combining behavioural filtering with pattern detection • Translating user journeys into SQL logic What stood out — Learning isn’t just about individual courses… it’s about the path between them. When you analyse sequences, you start seeing decisions — what comes next, and how often. That’s where the real insight lies. SQL isn’t just querying static data. It’s about tracking movement over time. Consistent learning, one query at a time 🚀 #SQL #LeetCode #SQLPractice #DataAnalytics #WindowFunctions #LearningInPublic

🚀 Day 7 of My SQL Learning Journey Today I learned about CASE WHEN in SQL, a powerful feature used to apply conditional logic inside SQL queries. It works similar to IF–ELSE logic in programming and helps transform raw data into meaningful insights. 📚 Topics Covered: 🔹 CASE WHEN (Conditional Logic) Learned how CASE WHEN is used to show different results based on conditions within a query. 🔹 SUM + CASE WHEN Practiced combining SUM with CASE WHEN to calculate totals for specific conditions, such as total sales for a particular product category. 🔹 COUNT + CASE WHEN Used COUNT with CASE WHEN to count rows that satisfy certain conditions, such as counting pass/fail students or active customers. 🔹 CASE WHEN Syntax Rules Understood that every CASE statement starts with CASE and ends with END, with conditions defined using WHEN and results returned using THEN. 🔹 CASE WHEN with GROUP BY Learned how CASE WHEN can be applied with GROUP BY to perform conditional calculations on grouped data. 🔹 CASE WHEN with WHERE Explored how CASE WHEN can help apply dynamic filtering conditions inside the WHERE clause. 💡 Key Learning: CASE WHEN allows us to add decision-making logic directly inside SQL queries, making it easier to create conditional calculations and customized reports. #SQL #SQLLearning #DataAnalytics #LearningJourney #Database #DataSkills

Excited to share an innovative and engaging way to master SQL: SQL Noir – where learning becomes an immersive detective adventure! 🕵️♂️ In SQL Noir, you step into the role of a detective, solving intriguing mysterious cases by writing precise SQL queries. Each challenge transforms complex database concepts into compelling story-driven puzzles that spark curiosity and make learning genuinely fun. Whether you're a beginner looking to build strong fundamentals or an experienced professional sharpening your skills, SQL Noir offers a refreshing approach that combines problem-solving, logical thinking, and storytelling. Highly recommended for anyone who wants to learn SQL in a more interactive and enjoyable way! #SQL #LearningSQL #GamifiedLearning #SQLNoir #DataSkills #ProfessionalDevelopment

**Day 9 of my 30 Days SQL Series 🚀** Today’s question was “Not Boring Movies” from LeetCode. At first, it looked like a simple filtering problem, but while solving it, I got stuck on a small concept. --- ### 💡 What the question was asking: We were given a table of movies with: * id * movie name * description * rating And we had to: 👉 select movies with **odd IDs** 👉 remove movies where description = **"boring"** 👉 sort the final result by **rating (highest first)** --- ### 😵💫 Where I got stuck: The condition for odd IDs was: `id % 2 = 1` I didn’t understand: 👉 why we are dividing by 2 👉 and what `%` actually does --- ### 🧠 What I understood: `%` is the **modulo operator**, which gives the remainder after division When we divide numbers by 2: * Even numbers → remainder = 0 * Odd numbers → remainder = 1 👉 So: `id % 2 = 1` means selecting **only odd IDs** --- ### ⚙️ Approach: * Used `% 2 = 1` to filter odd IDs * Removed rows where description = 'boring' * Sorted results using `ORDER BY rating DESC` --- ### 🧠 What I learned today: * `%` is not something to memorize, it’s a **logic to identify patterns** * Using 2 helps check even/odd, but `%` can be used with any number * Even simple questions can teach small but important concepts --- Today’s problem was easy, but it helped me understand the logic behind something I was just applying before. Learning step by step… 💪 #Day9 #SQL #LearningInPublic

🚀 Day 31 & 32 – SQL Learning Journey: CTEs & Recursive CTEs Over the past two days, I explored one of the most powerful features in SQL — Common Table Expressions (CTEs) and their advanced form, Recursive CTEs. 📌 Day 31: CTE Basics Learned how CTEs act as temporary result sets within a query, making complex SQL much easier to manage. ✨ Key Benefits: ✔ Improves query readability ✔ Encourages reusability ✔ Breaks complex logic into simpler steps 📌 Day 32: Recursive CTEs & Applications Dived deeper into recursion in SQL and explored practical use cases: 🔹 Generating sequences (e.g., numbers from 1 to 10) 🔹 Identifying missing values in a dataset 🔹 Working with hierarchical data (parent-child relationships) 💡 Core Concept: Recursive CTE = Base Query + Recursive Query → runs repeatedly until the condition is satisfied 📊 Key Insight: SQL can efficiently handle iterative and hierarchical problems without traditional loops, making it even more powerful for real-world data scenarios. 🔥 Consistency in learning is helping me build strong problem-solving skills in SQL step by step! #SQL #DataAnalytics #LearningJourney #CTE #RecursiveCTE #100DaysOfCode #DataAnalyst

💡 One SQL Lesson That Changed My Approach Recently, I realized that writing a query is easy… but writing an efficient query is the real skill. While working on a large dataset, I noticed performance issues. After optimizing indexes and rewriting joins, the query execution time dropped significantly 🚀 👉 Key takeaway: Always think beyond “working code” — focus on performance and scalability. #SQL #DataEngineering #Learning #CareerGrowth

🚀 Day 36 of My SQL Learning Journey Today I worked on a challenging SQL problem involving consecutive records and learned an important lesson along the way 🔥 🔹 Problem: Find records where people count is ≥ 100 for at least 3 consecutive entries 🔗 Problem Link: https://lnkd.in/gNBER5CQ 🔹 Final Solution: WITH temp AS ( SELECT id, visit_date, people, id - ROW_NUMBER() OVER (ORDER BY id) AS grp FROM Stadium WHERE people >= 100 ) SELECT id, visit_date, people FROM temp WHERE grp IN ( SELECT grp FROM temp GROUP BY grp HAVING COUNT(*) >= 3 ); 🔹 Key Learning 💡: The approach was to use ID-based grouping, because the problem depends on consecutive entries (IDs), not consecutive dates. 🔹 Concepts Used: ROW_NUMBER() for sequence handling Grouping consecutive records Window functions + aggregation 💡 Debugging mistakes helped me understand the problem more deeply than just solving it! Consistency continues 🚀 #SQL #LeetCode #WindowFunctions #ProblemSolving #90DaysOfCode #CodingJourney

🚀 Day 33/100 – SQL Practice (LeetCode) Today I worked on the problem “Find Followers Count” and strengthened my understanding of SQL aggregation. 🔹 What I Learned: Using GROUP BY to organize data effectively Applying COUNT() to calculate total values Understanding relationships between columns (user & followers) Writing clean and readable SQL queries Sorting results using ORDER BY for better clarity 🔹 Key Concept: Each user_id can have multiple follower_ids. By grouping data based on user_id, we can easily count the number of followers for each user. 🔹 SQL Solution: SELECT user_id, COUNT(follower_id) AS followers_count FROM Followers GROUP BY user_id ORDER BY user_id; 💡 Takeaway: Mastering simple problems builds a strong foundation in SQL. Small consistent efforts lead to big improvements over time! #Day33 #100DaysOfCode #SQL #LeetCode #DataLearning #PlacementPreparation