#sqlwithidc hasil pencarian

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 21 of #SQLWithIDC Challenge Complted! sponsored by @dpdzero & organized by @indiandataclub. 💡Today’s concept: CTEs — the best way to simplify complex SQL into clean, readable steps. 🎯 Challenge: Build a hospital performance dashboard using 3 CTEs + final performance.

𝐃𝐚𝐲 21/21 – 𝐒𝐐𝐋 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞🚀 🔸Learned CTEs today — clean, readable queries with step-by-step logic. 🔸Perfect for breaking down complex reports easily. 🔥 🔸CTEs > nested subqueries any day! ⚡ #SQLWithIDC #CTE #IndianDataClub #DPDzero

I did it! 21 Days of SQL. 21 Days of learning. 21 Days of consistency. Thanks @DPDzero and @IndianDataClub for making the journey so engaging. #SQLWithIDC #SQL #TechCommunity

Day - 20/21 days SQL challenge #SQlwithIDC @dpdzero Title Sponsor Back to the SQL grind as the challenge is about to end but learning many thing from the community and making few contributions which are visible in the community . Hope it continues with @indiandataclub

🗓️ Day 21 of #21DaysSQLChallenge by @indiandataclub! Today's topic: CTEs🎯 Using the WITH clause, you can create a temporary named result set & build your query step by step! Key takeaways💡 • Break complex queries into simple steps • Reuse logic • Easy to debug #SQLWithIDC

🌟 21 Days. 21 Chances to Grow. I just earned my 21-Day SQL Challenge Badge with #SQLWithIDC! 🚀 It’s not just a badge — it’s proof of showing up every day, learning, practicing, and building consistency. 💫 💭 Lesson: Progress > Perfection. Keep going, every day counts!

Day 19 — #21DaysSQLChallenge 🏥📊 Today’s task: Identify the Top 3 highest patient satisfaction weeks for each service. Ranking the best to make every week better 🔥 @dpdzero @indiandataclub #SQLWithIDC #SQL #HealthcareAnalytics #DataAnalytics #DPDzero #IndianDataClub #Day19

Day 19 #SQLWithIDC 🔶ROW_NUMBER(): Unique sequence for each row 🔷RANK(): Ties share rank, gaps appear 🔶DENSE_RANK(): Ties share rank, no gaps Use OVER() with PARTITION BY & ORDER BY to rank data fairly & powerfully. @indiandataclub @dpdzero

Day 21. Final day of the 21 Days of SQL Challenge. I built a dashboard with CTEs combining service metrics, staff metrics, and patient demographics, then computed a weighted performance score. @indiandataclub @dpdzero #SQL #SQLWithIDC

Day 20 #SQLWithIDC Window functions like SUM() OVER and AVG() OVER unlock running totals, moving averages, and cumulative stats no GROUP BY needed. Track trends, smooth data, and compare values in a single query. Power up your analytics! @indiandataclub @dpdzero

Day 21 — #21DaysSQLChallenge (Final Day!) 🚀 Wrapped up the challenge by building a full performance dashboard 1️⃣ Patient metrics 2️⃣ Service metrics 3️⃣ Staff metrics 21 days done — SQL muscles upgraded 💪 @dpdzero @indiandataclub #SQLWithIDC #SQL #DataAnalytics #Day21

𝐃𝐚𝐲 20 – #SQLWithIDC 🚀 Learnt window aggregates today — running totals & moving averages without losing rows. 📊 🔥 Quick picks: • SUM() OVER → running total • AVG() OVER → moving avg • Frame clause = control window Perfect for trends & time-series. 🙌

🗓️ Day 19 of #21DaysSQLChallenge by @indiandataclub! Today's topic was WINDOW FUNCTIONS!🖥️ These functions - - ROW_NUMBER() - RANK() - DENSE_RANK() ... let you analyze a row while still seeing the rest of the data. Unlike GROUP BY, nothing gets collapsed.🙌 #SQLWithIDC #SQL

🗓️ Day 20 of #21DaysSQLChallenge by @indiandataclub! Topic: Aggregate Window Functions! Key idea: calculate totals without losing rows Frame controls: UNBOUNDED PRECEDING = from start N PRECEDING = last N rows CURRENT ROW = this row N FOLLOWING = next N rows #SQLWithIDC #SQL

🕵️‍♀️ SQL Murder Mystery — Solved! ➡️All clues point to David Kumar - the only one in the CEO office during the crime, a false alibi, a suspicious call at 8:55 PM, and matching fingerprints. Sponsored by @DPDzero | Organized by @IndianDataClub #SQLWithIDC #21DaysSQLChallenge

✅Day 19 Completed – Window Functions Sponsored by @DPDzero and organized by @indiandataclub - Worked with ROW_NUMBER, RANK, DENSE_RANK using the OVER() clause to rank weekly satisfaction and pull the top 3 weeks per service. #SQLWithIDC

✅ Completed Day 20 - Window Functions Sponsored by @dpdzero & Organized by @indiandataclub. - Worked with running totals, moving averages, and trend analysis using SUM() OVER & AVG() OVER. - Analyzed weeks 10–20 for admissions + satisfaction trends. 🔍 #SQLWithIDC

Today’s Learning : SQL window functions. SUM() OVER for running totals, AVG() OVER for moving averages, and ROWS BETWEEN to control the window. Helps analyze trends without losing rows. #sqlwithidc #sqllearning #indiandataclub

📊 SQL Daily — Day 20 Trend analysis with cumulative counts, moving averages & service comparison (Weeks 10–20) 👇 📌 Cumulative + Moving Avg + Benchmarking = 🔥 Insights! on to D-Day 21🚀 @dpdzero @indiandataclub #SQLWithIDC #SQL #HealthcareAnalytics #DataAnalytics #Day20