Top Tweets for #30DaysofSQL
Keep practicing and be consistent! 📊
The more you practice, the more SQL starts to make sense. Don’t be afraid of mistakes — learn from them and keep going. 🙌🏽
#30DaysOfSQL #SQL #DataAnalytics
Day 6/30 💻
Busy day, so I didn’t get much studying done. 😭
But I updated my SQL Server and discovered new features like Copilot, Vector, Regex & AI. 🤖
Haven’t updated yours? This is your sign! Keep upgrading your skills. 📊✨
#30DaysOfSQL #SQL
Day 3/30 💻
Today was stressful and busy, but I still showed up. I learnt "ORDER BY", "AND", "OR" & "LIKE".
Just showing up makes a whole lot of difference. Stay consistent, even on your hardest days. ❤️
Hope this encourages someone today. ✨
#30DaysOfSQL #SQL
Day 2/30 💻
Today I learnt "INSERT INTO", "VALUES", "WHERE", "UPDATE", "SET", "DELETE" & "BETWEEN".
Learning with AI, my tutor’s videos @ezekiel_aleke & W3Schools. 📊
#30DaysOfSQL #SQL #DataAnalytics
🚨 30 Days of SQL 🚨
I’m learning SQL from scratch and documenting my journey for the next 30 days. 💻📊
I’ve learnt it before with my tutor @ezekiel_aleke ,but I’m learning it again to build stronger understanding.
Join me if you’re learning too! 🤝🏽
#30DaysOfSQL #SQL
New driver activation, one query :
WITH first_ride AS (
SELECT driver_id, MIN(ride_date) d
FROM rides GROUP BY driver_id)
Find drivers riding within days of signup 🚗
Day of SQL Interviews
#SQL #30DaysOfSQL
Day 25 of #30DaysOfSQL
I learned how powerful PARTITION BY is in SQL Server.
Unlike GROUP BY, it keeps all rows while adding totals and insights.
Example: show each employee’s salary + total salary of their department
Day 9 of my SQL Journey 💻
Hi #datafam, so today I decided to face my subquery fear and I started getting the hang of it. Subquery makes breaking down complex queries less scary
What’s your favorite SQL trick for handling tricky queries?
#30DaysOfSQL #Buildinginpublic
🧵 Day 1 of my #30DaysOfSQL Journey
Today I learned “Introduction to Databases & SQL.”
A database = organized collection of data.
SQL (Structured Query Language) = the language used to talk to databases.
Rules to remember:
Both queries must return the same number of columns
Data types must be compatible
#30DaysOfSQL #SQLServer #LearningInPublic
Day 20 of #30DaysOfSQL Set Operators in SQL Server
Sometimes, you need to compare results from 2 queries. Instead of joins, SQL gives us Set Operators
Let’s break them down 🧵
Hi everyone, here's the link to the project I created for the #30DaysOfSQL challenge. I'd love your thoughts and feedback. Thank you for engaging.
https://t.co/GfnXfMOSmy…
#learnwithmoyinofcanada #30SQLchallenge #Datacommunity
@cheftee_lead @Odunthedatagirl
It's day 30 of my 30 day SQL learning challenge, and it's been quite a journey. From struggling to import datasets into SQL Workbench and facing errors to mastering joins, subqueries, CTEs, and complex SQL functions that challenged my life choices.
Day 17 of #30DaysOfSQL LEFT JOIN vs RIGHT JOIN
What if you want all rows from one table
(even without a match)?🧵
🍋 Turning Lemons to Lemonade
Missed 4 days of my #30DaysOfSQL challenge. Work + Cider + DataCamp = overwhelming.
But… small wins still count. Progress isn’t perfect, it’s persistence. Back on track & ready to keep building.
#SQL #DataJourney #LearningInPublic
data-driven comparisons.
I’m excited to apply these concepts to real-world datasets! 🚀
#SQL #DataAnalytics #LearningInPublic #30DaysOfSQL @SQLServer
Day 14 of #30DaysOfSQL
Today I learned Subqueries → queries inside queries.
Think of it as: “Find X, then use X to find Y.”🧵
Day 6 of my #30DaysOfSQL Challenge
Yesterday we learned SELECT.
Today: Filters & Operators — the secret to pulling only the rows you need 🧵
Day 30 of #30DaysOfSQL
I wrapped up this challenge with a Top Customers table from the Sakila DB:
1.Shows Total spend & rentals per customer
2.Breaks rentals down by category
3.Includes JSON arrays of all rented films
4. Used window functions and CTEs
#datafam #techtwitter
Day 30 of #30DaysOfSQL
I wrapped up this challenge with a Top Customers table from the Sakila DB:
1. Shows Total spend & rentals per customer
2.Breaks rentals down by category
3.Includes JSON arrays of all rented films
4. Used window functions and CTEs
#datafam #techtwitter
Day X of #30DaysOfSQL 🚀
Today I explored ROLLUP in MySQL.
It’s like running multiple GROUP BY queries at once. It is perfect for subtotals & grand totals.
Task : Use Rollup to see payments by staff id and customer id
#datafam #techtwitter
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