SQL Challenge: Consecutive Numbers with LEAD Function

🚀#Day33/50 #LeetCodeChallenge Today I learned a powerful SQL pattern — Consecutive Rows / Sequence Detection 💡 Problem: Find numbers that appear at least 3 times consecutively in a table. 👉 This problem helped me understand how real-world data patterns are identified and analyzed. 🔍 Key Learnings: Using LAG() to access previous rows Difference between Self Join vs Window Functions How SQL can detect sequences and repeated patterns ⚡ Approaches I explored: Self Join (classic approach) Window Functions (optimized using LAG) 📌 Most important takeaway: Consecutive problems in SQL = ➡️ LAG / LEAD ➡️ ROW_NUMBER ➡️ Self Join 🧠 Practice Problems: Finding consecutive numbers Detecting sequences (like 1-2-3, 7-8) Real-world use cases (login streaks, attendance tracking) 🔥 Getting more confident with SQL patterns every day! #Day33 #SQL #DataAnalytics #LearningInPublic #100DaysOfCode #WindowFunctions #SelfJoin

NULL values are a common occurrence in datasets and require careful handling. Rarely, there is any dataset that does not have NULLs; it is like those things which you do not want to happen in life but are inevitable. But how do you handle NULLs in any given dataset using SQL? Below are some of the functions depends on the specific SQL database to make your work easier: 𝐈𝐅𝐍𝐔𝐋𝐋: Returns a specified value if the expression is NULL. This function returns the expression. 𝑬𝒙𝒂𝒎𝒑𝒍𝒆: 𝘐𝘍𝘕𝘜𝘓𝘓(𝘤𝘰𝘭𝘶𝘮𝘯_𝘯𝘢𝘮𝘦, '𝘥𝘦𝘧𝘢𝘶𝘭𝘵_𝘷𝘢𝘭𝘶𝘦') 𝐈𝐒𝐍𝐔𝐋𝐋: Takes two arguments and returns the second if the first is NULL. 𝑬𝒙𝒂𝒎𝒑𝒍𝒆: 𝘐𝘚𝘕𝘜𝘓𝘓(𝘤𝘰𝘭𝘶𝘮𝘯_𝘯𝘢𝘮𝘦, '𝘥𝘦𝘧𝘢𝘶𝘭𝘵_𝘷𝘢𝘭𝘶𝘦') 𝐍𝐔𝐋𝐋𝐈𝐅: Takes two parameters. If the two parameters are equal, then the function returns NULL, else it returns the first parameter. 𝑬𝒙𝒂𝒎𝒑𝒍𝒆: 𝘕𝘜𝘓𝘓𝘐𝘍(𝘤𝘰𝘭𝘶𝘮𝘯_𝘯𝘢𝘮𝘦, '𝘴𝘰𝘮𝘦 𝘷𝘢𝘭𝘶𝘦') 𝐂𝐎𝐀𝐋𝐄𝐒𝐂𝐄: Can handle multiple arguments, making it more flexible for handling a series of potential NULL values. 𝑬𝒙𝒂𝒎𝒑𝒍𝒆: 𝘊𝘖𝘈𝘓𝘌𝘚𝘊𝘌(𝘤𝘰𝘭𝘶𝘮𝘯_𝘈, 𝘤𝘰𝘭𝘶𝘮𝘯_𝘉) 𝐂𝐀𝐒𝐄 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭: This statements provide more flexibility for handling complex conditions. You can use them to achieve the same result as COALESCE. 𝑬𝒙𝒂𝒎𝒑𝒍𝒆: 𝘊𝘈𝘚𝘌 𝘞𝘏𝘌𝘕 𝘤𝘰𝘭𝘶𝘮𝘯_𝘯𝘢𝘮𝘦 𝘐𝘚 𝘕𝘜𝘓𝘓 𝘛𝘏𝘌𝘕 '𝘥𝘦𝘧𝘢𝘶𝘭𝘵_𝘷𝘢𝘭𝘶𝘦' 𝘌𝘓𝘚𝘌 𝘤𝘰𝘭𝘶𝘮𝘯_𝘯𝘢𝘮𝘦 𝘌𝘕𝘋 #SQL #dataquality #datahandling #dataengineering

✅ Solved a SQL problem on StrataScratch — Day 58 of my SQL Journey 💪 User activity looks random… until you track it over time 📅 Today’s challenge: identify users active for 3 consecutive days or more. The approach: • Removed duplicate activity using DISTINCT • Used LEAD() to access upcoming activity dates • Compared dates using DATE_ADD() • Identified continuous activity sequences What I practised: • Window functions (LEAD) • Date-based comparisons • Sequential pattern detection • Writing logic-driven queries What stood out — Patterns don’t exist in single rows. They exist across time. Once you think in sequences, user behaviour becomes much clearer. SQL isn’t just about querying data — It’s about understanding behaviour. Consistent learning, one query at a time 🚀 #SQL #StrataScratch #DataAnalytics #LearningInPublic #SQLPractice

don't wrt query 🚀 Day 34 – Top 50 SQL Questions Today’s problem: Product Price at a Given Date 🔍 Objective: Find the price of each product on a specific date. 💡 Approach: Used a correlated subquery to get the latest price before the given date Handled missing data using default values Focused on retrieving time-based records efficiently 📈 Key Insight: Selecting the most recent valid record is a key pattern in SQL interview questions. #SQL #DataAnalytics #LeetCode #ProblemSolving #Day34

🗓️ SQL Challenge Day #27: Biggest Single Number 🔹 Find the largest number that appears exactly once! 🔢 🔹 Problem:   Return the biggest "single" number (appears only once):   ✅ If no such number exists, return NULL  🔹 Solution:  SELECT     MAX(num) AS num FROM (     SELECT         num,         COUNT(1) AS cnt     FROM         MyNumbers     GROUP BY         num     HAVING         cnt = 1 ) t;   ✅ Result: Accepted  💡 Key Takeaway:   **MAX() handles NULL gracefully!** The outer query returns NULL automatically if the inner subquery finds no single numbers – no extra logic needed. This is cleaner than using CASE or IFNULL here.  👇 Your turn:   What’s your go-to pattern for handling "return NULL if empty result" scenarios in SQL?  #SQL #LeetCode #DataEngineering #ProblemSolving #Coding #LearningInPublic #Database #DataAnalytics

🚀 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

🌳 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

This SQL query runs perfectly. No errors. Clean logic. Looks correct. But the result is completely wrong. Look at the query in the image. It tries to calculate total revenue per customer. And at first glance, everything seems fine. But there’s a subtle mistake in the aggregation logic that completely distorts the output. This is exactly how production dashboards get incorrect numbers — not because queries fail, but because they silently return misleading results. Your challenge: What is wrong with this query? Write the correct SQL in the comments. Follow Data Rejected for real-world SQL challenges. Repost if this could help someone preparing for interviews or debugging production queries. Subscribe on YouTube for full SQL breakdowns. #SQL #DataEngineering #AnalyticsEngineering #DataAnalytics #Database #LearnSQL #SQLTips #TechCareers #QueryOptimization #BusinessIntelligence #DataRejected

In the context of SQL (Structured Query Language), a DATABASE is a systematic collection of structured data organized into tables consisting of rows and columns.

A SQL feature I don’t see used often: LATERAL (but very useful) While exploring some advanced SQL patterns, I came across LATERAL. It’s simple in idea, but powerful when dealing with row-wise logic. 🔹 What it does LATERAL lets a subquery refer to columns from the current row of the main query. 🔹 Example use case Get the latest order for each customer: SELECT c.customer_id, o.order_id, o.order_date FROM customers c CROSS APPLY ( SELECT order_id, order_date FROM orders o WHERE o.customer_id = c.customer_id ORDER BY order_date DESC FETCH FIRST 1 ROW ONLY ) o; 🔹 Why not a normal join? We can solve this using analytic functions or joins, but LATERAL makes it more direct for row-by-row dependent queries. 💡 What I found useful It simplifies queries where the inner logic depends on each row of the outer query — especially for “top N per group” type problems. Still exploring more use cases — Have you used LATERAL in your queries? #OracleSQL #SQL #DataEngineering #AdvancedSQL #DatabaseDevelopment