#30dayssql search results
It’s Day 25 of my #30DaysSQL challenge and today I moved into Exploratory Data Analysis on the Spotify dataset. I explored top artists by average popularity, songs that perform above their artist’s average, albums with the most tracks,
It’s Day 24 of my 30 Days SQL Learning Challenge, and today I focused on cleaning the Spotify dataset I’ve been working with. I standardized data types by converting release dates into proper DATE format and extracting release years.
Late night #30daysSQL After much shege with MySQL, I decided to stick with my PostgreSQL. I love it tho @cheftee_lead will understand Btw, I've heard different pronunciation of SQL, like Sequel, Sequeue, S-Que-L, See-queue, S-Q-L 😂😂😂 Add yours to it
📌 Day 18 of my #30DaysSQL Challenge Today, I explored some of the most practical window functions in SQL: 🔹 ROW_NUMBER() vs RANK() ROW_NUMBER() assigns a unique sequential number to rows (no ties).
It’s day 27 of my #30DaysSQL challenge, and today I focused on turning my Spotify project into a proper case study. I wrote queries that revealed deep business insights, like identifying artists who consistently outperform their genre peers using CTEs.
It’s Day 26 of my #30DaysSQL challenge and I didn’t do much work today. Instead, I focused on shaping my Spotify analysis into a proper portfolio project. I reviewed the queries I’ve written so far and explored how I could build a case study around the evolution of music
It’s Day 18 of my #30DaysSQL challenge and today I started learning Window Functions, which are also known as ranking functions. These functions help us rank rows using ROW_NUMBER(), RANK() & DENSE_RANK().
It’s day 17 of my 30days SQL learning challenge and I didn’t even open my laptop t. I honestly can’t tell why I wasn’t motivated to work on today’s task or I’d call today my cheat day 😂.
Day 7 #30daysSQL ✅SQL GROUP BY Statement ✅SQL HAVING Clause Then i did some practice questions on my sample database. SQL is fun!! Day 7 Done!!
📅Day count : 12/30 Days SQL challenge🔥 Today I Solved the Rank Scores problem no. 178 in LeetCode. #Leetcode #SQL #30DaysSQL #CodingJourney #dataAnalysis
It’s Day 8 of my #30DaysSQL challenge, and today I was very intentional about understanding how JOINs work and when to use the different types of JOINs. I asked ChatGPT to give me business questions from my Spotify data so I could write queries to answer them.
It’s Day 7 of my #30DayChallenge, and I couldn’t do much like that. I wanted to understand when and how to use the WHERE and HAVING filters, so I practiced writing queries with them. After that, I moved on to JOINs in SQL.
It’s Day 3 of my #30DaysSQL challenge and it really stretched me. I tried every possible way to import the CSV data into my SQL Workbench but kept encountering one error after another. I’ve been dealing with this since Day 1, hoping it was just a minor issue.
Day 2 of my #30DaysSQLChallenge I started today’s challenge by trying to fix the error I ran into yesterday using Python, but I ended up making things worse. 😅 I couldn’t do much querying because I had to go for my monthly biometric clearance, which was really exhausting.
It’s Day 19/30 of my #30DaysSQL challenge and today I continued practicing Window Functions but this time I combined them with Subqueries. I used subqueries in the FROM statement to create a temporary table where I could select and rank everything more easily.
It’s Day 18 of my #30DaysSQL challenge and today I started learning Window Functions, which are also known as ranking functions. These functions help us rank rows using ROW_NUMBER(), RANK() & DENSE_RANK().
📅 Day 17/30 Days SQL Challenge 🔥 Progress update: 🚀 - Explored Date Math Functions🧠 - HackerRank: Solved four SQL problems to boost my logical and analytical skills.✒️ Excited for the remaining days to continue building my SQL expertise!🔥 #SQL #30DaysSQL #DataAnalysis
It’s day 28 of my #30daysSQL and today was a learning free day for me because I didn’t open my laptop. But then, I still made some research on the right way to document a portfolio project in SQL. By tomorrow i should have been able to finish up with it.
It’s day 27 of my #30DaysSQL challenge, and today I focused on turning my Spotify project into a proper case study. I wrote queries that revealed deep business insights, like identifying artists who consistently outperform their genre peers using CTEs.
It’s Day 26 of my #30DaysSQL challenge and I didn’t do much work today. Instead, I focused on shaping my Spotify analysis into a proper portfolio project. I reviewed the queries I’ve written so far and explored how I could build a case study around the evolution of music
It’s Day 25 of my #30DaysSQL challenge and today I moved into Exploratory Data Analysis on the Spotify dataset. I explored top artists by average popularity, songs that perform above their artist’s average, albums with the most tracks,
It’s day 28 of my #30daysSQL and today was a learning free day for me because I didn’t open my laptop. But then, I still made some research on the right way to document a portfolio project in SQL. By tomorrow i should have been able to finish up with it.
It’s day 27 of my #30DaysSQL challenge, and today I focused on turning my Spotify project into a proper case study. I wrote queries that revealed deep business insights, like identifying artists who consistently outperform their genre peers using CTEs.
It’s day 27 of my #30DaysSQL challenge, and today I focused on turning my Spotify project into a proper case study. I wrote queries that revealed deep business insights, like identifying artists who consistently outperform their genre peers using CTEs.
It’s Day 26 of my #30DaysSQL challenge and I didn’t do much work today. Instead, I focused on shaping my Spotify analysis into a proper portfolio project. I reviewed the queries I’ve written so far and explored how I could build a case study around the evolution of music
It’s Day 26 of my #30DaysSQL challenge and I didn’t do much work today. Instead, I focused on shaping my Spotify analysis into a proper portfolio project. I reviewed the queries I’ve written so far and explored how I could build a case study around the evolution of music
It’s Day 25 of my #30DaysSQL challenge and today I moved into Exploratory Data Analysis on the Spotify dataset. I explored top artists by average popularity, songs that perform above their artist’s average, albums with the most tracks,
It’s Day 25 of my #30DaysSQL challenge and today I moved into Exploratory Data Analysis on the Spotify dataset. I explored top artists by average popularity, songs that perform above their artist’s average, albums with the most tracks,
It’s Day 24 of my 30 Days SQL Learning Challenge, and today I focused on cleaning the Spotify dataset I’ve been working with. I standardized data types by converting release dates into proper DATE format and extracting release years.
📌 Day 18 of my #30DaysSQL Challenge Today, I explored some of the most practical window functions in SQL: 🔹 ROW_NUMBER() vs RANK() ROW_NUMBER() assigns a unique sequential number to rows (no ties).
It’s Day 19/30 of my #30DaysSQL challenge and today I continued practicing Window Functions but this time I combined them with Subqueries. I used subqueries in the FROM statement to create a temporary table where I could select and rank everything more easily.
It’s Day 18 of my #30DaysSQL challenge and today I started learning Window Functions, which are also known as ranking functions. These functions help us rank rows using ROW_NUMBER(), RANK() & DENSE_RANK().
It’s Day 18 of my #30DaysSQL challenge and today I started learning Window Functions, which are also known as ranking functions. These functions help us rank rows using ROW_NUMBER(), RANK() & DENSE_RANK().
It’s day 17 of my 30days SQL learning challenge and I didn’t even open my laptop t. I honestly can’t tell why I wasn’t motivated to work on today’s task or I’d call today my cheat day 😂.
It’s Day 8 of my #30DaysSQL challenge, and today I was very intentional about understanding how JOINs work and when to use the different types of JOINs. I asked ChatGPT to give me business questions from my Spotify data so I could write queries to answer them.
It’s Day 7 of my #30DayChallenge, and I couldn’t do much like that. I wanted to understand when and how to use the WHERE and HAVING filters, so I practiced writing queries with them. After that, I moved on to JOINs in SQL.
#SQL #30DaysSQL #DataAnalytics #LearningInPublic #DataJourney #KeepGoing #NeverGiveUp #learnwithmoyinofcanada
It’s Day 3 of my #30DaysSQL challenge and it really stretched me. I tried every possible way to import the CSV data into my SQL Workbench but kept encountering one error after another. I’ve been dealing with this since Day 1, hoping it was just a minor issue.
Day 2 of my #30DaysSQLChallenge I started today’s challenge by trying to fix the error I ran into yesterday using Python, but I ended up making things worse. 😅 I couldn’t do much querying because I had to go for my monthly biometric clearance, which was really exhausting.
📅 Day 17/30 Days SQL Challenge 🔥 Progress update: 🚀 - Explored Date Math Functions🧠 - HackerRank: Solved four SQL problems to boost my logical and analytical skills.✒️ Excited for the remaining days to continue building my SQL expertise!🔥 #SQL #30DaysSQL #DataAnalysis
📅Day count : 12/30 Days SQL challenge🔥 Today I Solved the Rank Scores problem no. 178 in LeetCode. #Leetcode #SQL #30DaysSQL #CodingJourney #dataAnalysis
Late night #30daysSQL After much shege with MySQL, I decided to stick with my PostgreSQL. I love it tho @cheftee_lead will understand Btw, I've heard different pronunciation of SQL, like Sequel, Sequeue, S-Que-L, See-queue, S-Q-L 😂😂😂 Add yours to it
Late night #30daysSQL After much shege with MySQL, I decided to stick with my PostgreSQL. I love it tho @cheftee_lead will understand Btw, I've heard different pronunciation of SQL, like Sequel, Sequeue, S-Que-L, See-queue, S-Q-L 😂😂😂 Add yours to it
Day 7 #30daysSQL ✅SQL GROUP BY Statement ✅SQL HAVING Clause Then i did some practice questions on my sample database. SQL is fun!! Day 7 Done!!
📌 Day 18 of my #30DaysSQL Challenge Today, I explored some of the most practical window functions in SQL: 🔹 ROW_NUMBER() vs RANK() ROW_NUMBER() assigns a unique sequential number to rows (no ties).
📅Day count : 12/30 Days SQL challenge🔥 Today I Solved the Rank Scores problem no. 178 in LeetCode. #Leetcode #SQL #30DaysSQL #CodingJourney #dataAnalysis
It’s Day 25 of my #30DaysSQL challenge and today I moved into Exploratory Data Analysis on the Spotify dataset. I explored top artists by average popularity, songs that perform above their artist’s average, albums with the most tracks,
It’s Day 24 of my 30 Days SQL Learning Challenge, and today I focused on cleaning the Spotify dataset I’ve been working with. I standardized data types by converting release dates into proper DATE format and extracting release years.
📅 Day 17/30 Days SQL Challenge 🔥 Progress update: 🚀 - Explored Date Math Functions🧠 - HackerRank: Solved four SQL problems to boost my logical and analytical skills.✒️ Excited for the remaining days to continue building my SQL expertise!🔥 #SQL #30DaysSQL #DataAnalysis
It’s Day 18 of my #30DaysSQL challenge and today I started learning Window Functions, which are also known as ranking functions. These functions help us rank rows using ROW_NUMBER(), RANK() & DENSE_RANK().
It’s day 17 of my 30days SQL learning challenge and I didn’t even open my laptop t. I honestly can’t tell why I wasn’t motivated to work on today’s task or I’d call today my cheat day 😂.
It’s day 27 of my #30DaysSQL challenge, and today I focused on turning my Spotify project into a proper case study. I wrote queries that revealed deep business insights, like identifying artists who consistently outperform their genre peers using CTEs.
It’s Day 26 of my #30DaysSQL challenge and I didn’t do much work today. Instead, I focused on shaping my Spotify analysis into a proper portfolio project. I reviewed the queries I’ve written so far and explored how I could build a case study around the evolution of music
It’s Day 19/30 of my #30DaysSQL challenge and today I continued practicing Window Functions but this time I combined them with Subqueries. I used subqueries in the FROM statement to create a temporary table where I could select and rank everything more easily.
It’s Day 18 of my #30DaysSQL challenge and today I started learning Window Functions, which are also known as ranking functions. These functions help us rank rows using ROW_NUMBER(), RANK() & DENSE_RANK().
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