#50daysofsql Suchergebnisse
Day 6: Using left join, I joined the Employees table to the EmployeeUNI table in order to obtain all records in Employees and their corresponding unique ID, and to set the unique ID of employees with no unique ID to NULL. Aliases increased runtime so I removed them🤧 #50daysofsql
Had my birthday and @alx_africa data viz task to deal with, hence the three day hiatus👉👈 Day 5: I applied the LENGTH function to count the number of characters in the tweet content to determine whether it's valid or invalid #50daysofsql
Day 2: I initially didn't attach the OR statement until I checked the table and saw NULL referee ids. #50daysofsql
Day 7: Still on easy challenges, first time beating 95% users on runtime #50daysofsql
Day 6: Using left join, I joined the Employees table to the EmployeeUNI table in order to obtain all records in Employees and their corresponding unique ID, and to set the unique ID of employees with no unique ID to NULL. Aliases increased runtime so I removed them🤧 #50daysofsql
Day 18 of Mastering SQL - Solving a MEDIUM level question. 🔥 Beats 88.4% submissions #SQL #50daysofsql
Day 8: I forgot to use GROUPBY for aggregation for over 30 minutes, kept looking for syntax error before my head boot las las🤧 #50daysofsql
Had my birthday and @alx_africa data viz task to deal with, hence the three day hiatus👉👈 Day 5: I applied the LENGTH function to count the number of characters in the tweet content to determine whether it's valid or invalid #50daysofsql
💻 Day 2/50: LeetCode SQL Challenge Solved 584: Find Customer Referee today! 🎯 ✅ Learned to filter data using WHERE + IS NOT NULL. ✅ Focused on retrieving non-NULL referee_id values. Key takeaway: Precision in filtering makes all the difference! 🚀 #50DaysOfSQL #LeetCode
Day 3/50: Solved "Big Countries" on LeetCode! 🌍✨ 📝 Find countries with: ✅ Population ≥ 25M ✅ Area ≥ 3M km² #50DaysOfSQL #LeetCode #DataSkills #SQL
✅ Day 5 of #50DaysOfSQL: Solved a problem where I removed employees with non-unique IDs and replaced them with NULL. 🛠️ Great practice with SQL queries like JOIN, GROUP BY, and HAVING! On to the next challenge! 🚀 #SQL #LeetCode #DataScience #CodingJourney
Day 15 of #50DaysOfSQL ✅ Learned the magic of 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀: • Ranked rows using ROW_NUMBER() & RANK() • Calculated running totals with SUM() • Used LAG() & LEAD() to compare rows • Applied moving averages for trends Solved 1 question on HackerRank
Day 13 of #50DaysOfSQL ✅ Learned 𝗦𝗲𝘁 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: • UNION/UNION ALL: Combine datasets • INTERSECT: Find common rows • EXCEPT: Compare differences #LearningInPublic #SQL #DataSkills
Day R4 of SQL Revision Sprint! (Reviewing Days 13–16 of #50DaysOfSQL) • Set operations: UNION, INTERSECT, EXCEPT • Non-Equi Joins • Window Functions: RANK(), ROW_NUMBER() One more revision day to go before jumping back in full swing! #LearnInPublic #SQLChallenge #DataSkills
Day R3 of SQL Revision Sprint! (Reviewing Days 9–12 of #50DaysOfSQL) • Nested Subqueries • Mastered Joins: INNER, LEFT, RIGHT, FULL OUTER • Self-Joins & Cross-DB joins • Revisited Mini-Project 2: Sales & Shipping Insights One JOIN at a time! #SQL #LearnInPublic #DataSkills
Day R2 of SQL Revision Sprint! (Reviewing Days 5–8 of #50DaysOfSQL) • Revisited my 1st mini-project: Invoicing system analysis • Refreshed string/date/numeric functions • Grouped & aggregated data • GROUP BY, HAVING, nested CONCAT #LearnInPublic #DataSkills #DataAnalytics
Restarting my #50DaysOfSQL journey with a 5-day revision sprint! Day R1: • SQL Basics • Filtering with WHERE, IN, LIKE • Sorting + DISTINCT • Practice queries to warm up 🔥 Back in query mode after a 4-month break 😅 Let’s go! 🚀 #LearningInPublic #SQLChallenge #DataSkills
Day 20 of #50DaysOfSQL ✅ Mastered Recursive Queries for: • Organizational hierarchies 🔗 • Summing numbers ➕ • Directory trees 🗂️ Recursive queries make hierarchical data analysis a breeze! Solved 6 questions on HackerRank today 🚀 #LearningInPublic #SQL #DataSkills
Day 19 of #50DaysOfSQL Explored the magic of 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀: • WHERE: Dynamic filtering • FROM: Derived tables • SELECT: Calculated metrics • Correlated Subqueries: Row-by-row comparisons #LearnInPublic #SQL #DataSkills
Day 18 of #50DaysOfSQL After a break, I'm restarting the series! 🚀 Spent today revising everything I’ve covered so far, from basic queries to window functions. Feeling ready to dive back into learning new concepts tomorrow! #SQL #LearnInPublic #DataSkills #SQLChallenge
✅ Day 5 of #50DaysOfSQL: Solved a problem where I removed employees with non-unique IDs and replaced them with NULL. 🛠️ Great practice with SQL queries like JOIN, GROUP BY, and HAVING! On to the next challenge! 🚀 #SQL #LeetCode #DataScience #CodingJourney
Day 3/50: Solved "Big Countries" on LeetCode! 🌍✨ 📝 Find countries with: ✅ Population ≥ 25M ✅ Area ≥ 3M km² #50DaysOfSQL #LeetCode #DataSkills #SQL
💻 Day 2/50: LeetCode SQL Challenge Solved 584: Find Customer Referee today! 🎯 ✅ Learned to filter data using WHERE + IS NOT NULL. ✅ Focused on retrieving non-NULL referee_id values. Key takeaway: Precision in filtering makes all the difference! 🚀 #50DaysOfSQL #LeetCode
Day 17 of #50DaysOfSQL ✅ Mastered 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀: • Running Totals 📊 • Percentiles (PERCENT_RANK(), CUME_DIST()) 🏅 • Moving Averages 📈 • First & Last Values 🔍 Solved 1 questions on @hackerrank just keeps getting better! 🚀
Day 16 of #50DaysOfSQL ✅ Revision day! Spent time reviewing everything from basic queries to window functions. Feels great to solidify the foundation before diving deeper. 🚀 #LearningInPublic #SQL #DataSkill
Day 15 of #50DaysOfSQL ✅ Learned the magic of 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀: • Ranked rows using ROW_NUMBER() & RANK() • Calculated running totals with SUM() • Used LAG() & LEAD() to compare rows • Applied moving averages for trends Solved 1 question on HackerRank
Day 14 of #50DaysOfSQL Mastered 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗝𝗼𝗶𝗻𝘀: • Self-Joins: Compare rows within the same table • Cross-DB Joins: Combine multiple databases • Non-Equi Joins: Map ranges with BETWEEN Solved 1 question on @hackerrank just keeps getting better!
Day 6: Using left join, I joined the Employees table to the EmployeeUNI table in order to obtain all records in Employees and their corresponding unique ID, and to set the unique ID of employees with no unique ID to NULL. Aliases increased runtime so I removed them🤧 #50daysofsql
Had my birthday and @alx_africa data viz task to deal with, hence the three day hiatus👉👈 Day 5: I applied the LENGTH function to count the number of characters in the tweet content to determine whether it's valid or invalid #50daysofsql
Day 7: Still on easy challenges, first time beating 95% users on runtime #50daysofsql
Day 6: Using left join, I joined the Employees table to the EmployeeUNI table in order to obtain all records in Employees and their corresponding unique ID, and to set the unique ID of employees with no unique ID to NULL. Aliases increased runtime so I removed them🤧 #50daysofsql
Day 2: I initially didn't attach the OR statement until I checked the table and saw NULL referee ids. #50daysofsql
Day 8: I forgot to use GROUPBY for aggregation for over 30 minutes, kept looking for syntax error before my head boot las las🤧 #50daysofsql
Had my birthday and @alx_africa data viz task to deal with, hence the three day hiatus👉👈 Day 5: I applied the LENGTH function to count the number of characters in the tweet content to determine whether it's valid or invalid #50daysofsql
Day 18 of Mastering SQL - Solving a MEDIUM level question. 🔥 Beats 88.4% submissions #SQL #50daysofsql
✅ Day 5 of #50DaysOfSQL: Solved a problem where I removed employees with non-unique IDs and replaced them with NULL. 🛠️ Great practice with SQL queries like JOIN, GROUP BY, and HAVING! On to the next challenge! 🚀 #SQL #LeetCode #DataScience #CodingJourney
Day 3/50: Solved "Big Countries" on LeetCode! 🌍✨ 📝 Find countries with: ✅ Population ≥ 25M ✅ Area ≥ 3M km² #50DaysOfSQL #LeetCode #DataSkills #SQL
💻 Day 2/50: LeetCode SQL Challenge Solved 584: Find Customer Referee today! 🎯 ✅ Learned to filter data using WHERE + IS NOT NULL. ✅ Focused on retrieving non-NULL referee_id values. Key takeaway: Precision in filtering makes all the difference! 🚀 #50DaysOfSQL #LeetCode
Day 17 of #50DaysOfSQL ✅ Mastered 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀: • Running Totals 📊 • Percentiles (PERCENT_RANK(), CUME_DIST()) 🏅 • Moving Averages 📈 • First & Last Values 🔍 Solved 1 questions on @hackerrank just keeps getting better! 🚀
Day 9 of #50DaysOfSQL Learned 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗚𝗿𝗼𝘂𝗽𝗶𝗻𝗴 & 𝗡𝗲𝘀𝘁𝗲𝗱 𝗤𝘂𝗲𝗿𝗶𝗲𝘀: • Grouped by multiple columns (e.g., client + year) • Filtered data with subqueries • Built virtual tables for deeper analysis Solved x questions on @HackerRank #LearningInPublic
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