Day2️⃣1️⃣of 21 Day SQL Challenge by @indiandataclub & @dpdzero Topics: WITH clause, CTEs, recursive CTEs CTEs create temporary named result sets that exist only during query execution. They make complex queries more readable and maintainable. #SQL #SQLWithIDC #21DaysOfSQL

Day2️⃣0️⃣of 21 Day SQL Challenge by @indiandataclub & @dpdzero Topics: SUM() OVER, AVG() OVER, running totals, moving averages Aggregate window functions calculate running totals, moving averages, and cumulative statistics without collapsing rows. #SQL #SQLWithIDC #21DaysOfSQL

Day1️⃣9️⃣of 21 Day SQL Challenge by @indiandataclub & @dpdzero Topics: ROW_NUMBER(), RANK(), DENSE_RANK(), OVER clause Window functions perform calculations across rows related to the current row, without collapsing results like GROUP BY. #SQL #SQLWithIDC #21DaysOfSQL

Day1️⃣8️⃣ of 21 Day SQL Challenge by @indiandataclub & @dpdzero Topics: UNION, UNION ALL, combining result sets, UNION combines results from multiple SELECT statements into a single result set. #SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic

Day1️⃣7️⃣ of 21 Day SQL Challenge by @indiandataclub & @dpdzero Topics: Subqueries in SELECT, derived tables, and inline views. Used subqueries with SELECT and FROM to get calculated columns and drive tables from data. #SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL

Day1️⃣6️⃣ of 21 Day SQL Challenge by @indiandataclub & @dpdzero Topics: Subqueries in WHERE, nested queries, filtering with subqueries Subqueries are queries nested inside other queries. #SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic #Joins

total patients admitted that week, total patients refused, average patient satisfaction, count of staff assigned to service, and count of staff present that week. Order by patients admitted descending. #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic

Day 1️⃣4️⃣/21 Day SQL Challenge by @indiandataclub Sponsored by @dpdzero Getting back on track. Revised JOINS, focusing on LEFT JOIN and RIGHT JOIN Observation: - Nurses and nurse assistants are present more than doctors; all 5 staff members #SQL #SQLWithIDC #21DaysOfSQL

🔍 Observation: - ICU is the most staffed service (48 staff) - Emergency follows with 29 staff - All services meet the staffing threshold (>5) #SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic #NULLHandling #INNERJOIN

Day 11 of #21DaysOfSQL by @indiandataclub sponsored by @dpdzero. Practiced DISTINCT, handling duplicates, and counting unique service–event combinations. Found flu as the most common event across services, with general medicine leading. #SQLWithIDC #21DaysOfSQL #DataAnalytics

Day 🔟/ #21DaysOfSQL with @indiandataclub & @dpdzero Used CASE + GROUP BY to build a service performance report. All services scored 77–82, landing in the “Good” category. Solid performance, with scope to push toward “Excellent.” #SQLWithIDC #21DaysOfSQL #DataAnalytics #MYSQL

Day 9️⃣ of #21DaysOfSQL with @IndianDataClub & @dpdzero Practiced DATE functions & date arithmetic 📅 Built a query to find services with avg hospital stay > 7 days. Surgery stays longest, Emergency sees highest patient count. #SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL

Day 7⃣ of 21 SQL Challenge by @indiandataclub and @dpdzero Not feeling great, but showed up. Practiced HAVING—used after GROUP BY to filter aggregates (not rows like WHERE). Found Emergency & Surgery with >100 refusals and avg satisfaction <80. #SQLWithIDC #21DaysOfSQL #MySQL

Day 6️⃣ of 21 SQL Challenge by @indiandataclub and @dpdzero Past midnight but still learning Revised GROUP BY in MySQL for hospital data. ICU had the highest admission rate (82.13%), Emergency had the lowest (19.13%). #SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL

Day 5️⃣ | 21-Day SQL Challenge Practiced on aggregate functions & data summarization in MySQL. 🔹 Practiced: COUNT(), AVG(), MIN(), MAX(), SUM(), ROUND() 🔹 Daily Challenge: Total patients admitted, total refused & avg satisfaction (2 decimals) #SQL #SQLWithIDC #21DaysOfSQL

Day 4️⃣ of 21 Days of SQL by @indiandataclub (sponsored by @dpdzero ) 🚀 Focused on OFFSET & LIMIT for sorting, ranking, and top-N analysis. Challenge: Retrieved the top 5 weeks with the highest patient refusals across services 📊 #SQL #SQLWithIDC #21DaysOfSQL

Day 3️⃣ of 21 Day SQL Challenge by @indiandataclub sponsored by @dpdzero Focus: ORDER BY & LIMIT * Sorted data using ORDER BY (single & multi-column) * Used LIMIT for top-N analysis * Learned how sorting supports ranking & performance insights #SQL #SQLWithIDC #21DaysOfSQL

- Applied LIMIT to fetch the top 10 records from the services_weekly table Challenge for DAY 1: List all unique hospital services available in the hospital. " SELECT DISTINCT (service) FROM services_weekly; " #SQL #SQLWithIDC #21DaysOfSQL

The dataset includes patient details, weekly hospital services, and staff schedules in CSV format. For practice, I: - Used SELECT with " * " to retrieve all records from the patients table, - Selected specific columns using column names, #SQL #SQLWithIDC #21DaysOfSQL