#sqlwithidc kết quả tìm kiếm
Day 12 #SQLWithIDC In SQL, NULL is not a value it’s the silence between the notes. It’s the unknown, the missing, the unrecorded. IS NULL, IS NOT NULL, COALESCE() these are not just keywords, they’re the tools to give meaning to absence. @indiandataclub @dpdzero
Day 14 #SQLWithIDC INNER JOIN seeks alignment LEFT JOIN preserves perspective RIGHT JOIN changes it A NULL in a LEFT JOIN isn’t absence — it’s a story untold, a connection yet to be made Data reminds us: inclusion reveals as much as matching ever will @indiandataclub @dpdzero
Day 10 of #SQLWithIDC 🚀— CASE statements 💡 Key takeaways: • Use CASE to categorize or create conditional metrics • Always include ELSE (avoid NULLs) • Works in SELECT, ORDER BY, and GROUP BY • First match wins — order matters!
Day 13 #SQLWithIDC In SQL and life, INNER JOIN reminds us: True insight emerges where paths intersect. It’s not about gathering all data— But about finding meaningful matches that matter. Real connection, real value. @indiandataclub @dpdzero
𝗗𝗮𝘆 12 #21DaysSQLChallenge 🚀 Handling NULLs & comparing categories ✅ IS NULL / IS NOT NULL ✅ COALESCE for fallback ✅ COUNT(*) vs COUNT(column) ✅ CTE + CASE for clean summaries ⚠️ Don’t treat NULL as a value Stepwise queries = clear & scalable SQL! 🙌 #SQLWithIDC
Day 12 ✅ of #21DaysSQLChallenge by @IndianDataClub x @DPDzero Dived into NULL handling. Today’s challenge: compare weeks “With Event” vs “No Event” and analyze satisfaction + morale. Key learning: NULLs change everything—handle them smartly! #SQLWithIDC
Day 21 #SQLWithIDC CTEs transform tangled logic into elegant, reusable steps, turning complexity into insight. From simple stats to multi-step analysis, CTEs are a game-changer for query organization. @indiandataclub @dpdzero
𝗗𝗮𝘆 𝟭𝟴 #SQLWithIDC🚀 Today I explored UNION & UNION ALL — combining multiple queries into one dataset! ✨ 💡Quick Tips: • UNION = no duplicates✅ • UNION ALL = keeps all✅ • Match columns & types • Order only after final result Combine smartly, analyze faster! 🙌
Day 10 | #21DaysSQLChallenge with @indiandataclub & @dpdzero Learned conditional logic with CASE WHEN: 🔹 Categorised satisfaction levels 🔹 Grouped staff roles 💡 Challenge: Classify services as Excellent, Good, Fair, or Needs Improvement #SQLWithIDC #SQL #DataAnalytics
Day 18 #SQLWithIDC 🔶UNION removes duplicates, slower but unique results. 🔷UNION ALL keeps all rows, faster performance. 🔶Same columns + compatible types. Use ORDER BY last. Pro tip: Use UNION ALL when duplicates aren't an issue! @indiandataclub @dpdzero
Day 11 #SQLWithIDC 🔶DISTINCT removes duplicates, showing unique rows based on all selected columns. 🔷Use it to clean data and get true unique values. 🔶Remember, for aggregates use GROUP BY, and handle duplicates early for better performance. @indiandataclub @dpdzero
🚀 𝐃𝐚𝐲 19 — 𝐈𝐃𝐂 𝐒𝐐𝐋 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 Window functions unlocked today! 🔍 ROW_NUMBER = unique RANK = ties with gaps DENSE_RANK = ties without gaps ✨Perfect for top-N insights & performance ranking📊 #SQLWithIDC
Day 12 of #21DaysSQLChallenge by @IndianDataClub & @dpdzero 🔹 Topic: NULL Handling Learned how to work with missing data using IS NULL, IS NOT NULL, and COALESCE() to replace NULLs and ensure accurate filtering and calculations. #SQLWithIDC #LearnSQL #IDCChallenge
🚀 Day 1 of the IDC 21 Days SQL Challenge! Started my journey with basics: SELECT, filtering, exploring tables & finding unique values with DISTINCT. Day 1 challenge: List all unique hospital services. Big thanks to IDC & @dpdzero for the supportive community!🙌 #SQLWithIDC
Day 10 of the #21DaysSQLChallenge with @indiandataclub! Today’s topic: CASE statements — SQL’s if-else logic.💻 ✅Perfect for adding decisions inside your queries ✅Super handy for creating categories, custom sorting, and conditional summaries!✨ #SQLWithIDC #SQL #Data
day -18/21 Days SQl challenge #SQLwithIDC Getting back to the Grind of SQL with @indiandataclub and @dpdzero
Completed 7 days of the 21 Days SQL Challenge. Staying consistent has helped me strengthen my foundation and approach problems with clarity. Looking forward to learning more and progressing further in the upcoming days. Tagging @dpdzero and @indiandataclub #SQLWithIDC
Day 10/21 days sql challenge #SQLwithIDC SELECT SERVICE,COUNT(*) AS total_patients_admitted,AVG(SATISFACTION) AS avg_satisfactionCASE AVG(SATISFACTION) >= 85 'Excellent' AVG(SATISFACTION) >= 75 'Good' AVG(SATISFACTION) >= 65 'Fair' ELSE 'Needs Improvement'END AS pc FROM patients
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