#30daysofsql ผลการค้นหา

Day 27 of my #30DaysOfSQL Stored Procedures vs Functions, finally making sense. Today I focused on SQL Functions, and they were confusing at first. The breakthrough came when I understood this simple idea: Stored procedures PERFORM tasks. Functions RETURN results.

DAY 13 of my SQL Journey Today is about learning window functions row_number(), rank() and how partition by works. It was a bit confusing at first but with some examples I tried it started making sense. Slowly getting there. #30DaysOfSQL #DataAnalytics

Day 26 of #30DaysOfSQL CTEs just made SQL make sense Today I learned how Common Table Expressions (CTEs) break complex logic into simple, readable steps. Instead of stuffing everything into one massive query, a CTE lets you think in layers.

Day 10/30 Today was all about string functions left, substring, replace, charindex e.t.c . These functions are powerful for cleaning, formatting, and preparing data for analysis. Which SQL function do you think is underrated but super useful? #30DaysOfSQL #buildinginpublic

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 23 of #30DaysOfSQL Today I learned about Views in SQL Server and honestly, this feels like a mini superpower. A View is basically a saved SQL query that behaves like a virtual table. It makes your work cleaner, faster, and more consistent.

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

I’m starting #30DaysOfSQL today! 💪 For the next 30 days, I’ll share 1 SQL concept daily — from basics to advanced. Short. Practical. Easy to learn. Follow along and bookmark this thread 👇 Let’s make SQL fun again! 💙 #SQL #DataAnalytics #DataScience #LearnSQL

🧵 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.

I’ll be sharing daily progress, resources, and lessons learned along the way. If you’re learning SQL too, let’s connect and grow together!✍️🫡 #SQL #DataAnalytics #30DaysOfSQL

Day 22 of #30DaysOfSQL Understanding Indexes in SQL Server ⚡ Indexes make queries faster by helping SQL Server find data without scanning the whole table. Think of an index as a table of contents for your data. 🧵

Day 21 of #30DaysOfSQL Nested Joins + Subqueries in Joins (SQL Server Edition) I’ve joined 2 tables before, now let’s link 3 or 4+ 💪🧵

Little win in my #30DaysOfSQL journey: I just switched from MySQL → SQL Server & wow, I see the flavours of SQL clearly now. ✅ MySQL: simple, great start ✅ SQL Server: richer (INTERSECT, EXCEPT, CTEs, window funcs) Even small syntax shifts = big growth. Loving it! #sql

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. github.com/Elizabeth-moyi… #learnwithmoyinofcanada #30SQLchallenge #Datacommunity @cheftee_lead @Odunthedatagirl

Key takeaway: Self-joins let you explore hierarchies within one table. #SQL #30DaysOfSQL #LearningInPublic #DataAnalytics

Day 19 of #30DaysOfSQL Self-Joins Sometimes the data you need is in one table. That’s when we use a Self-Join. 🧵

Recap: INNER JOIN → only matches LEFT JOIN → all left RIGHT JOIN → all right FULL JOIN → simulate with UNION CROSS JOIN → all combos #SQL #MySQL #30DaysOfSQL #LearningInPublic

Day 18 of #30DaysOfSQL — FULL JOIN & CROSS JOIN (MySQL) MySQL doesn’t support FULL JOIN directly. But here’s how to handle it 🧵

#30DaysofSQL #ALX_DS

Little win in my #30DaysOfSQL journey: I just switched from MySQL → SQL Server & wow, I see the flavours of SQL clearly now. ✅ MySQL: simple, great start ✅ SQL Server: richer (INTERSECT, EXCEPT, CTEs, window funcs) Even small syntax shifts = big growth. Loving it! #sql

Day 22 of #30DaysOfSQL Understanding Indexes in SQL Server ⚡ Indexes make queries faster by helping SQL Server find data without scanning the whole table. Think of an index as a table of contents for your data. 🧵

Day 23 of #30DaysOfSQL Today I learned about Views in SQL Server and honestly, this feels like a mini superpower. A View is basically a saved SQL query that behaves like a virtual table. It makes your work cleaner, faster, and more consistent.

Day 13 of #30DaysOfSQL Today → Logical Operators for smarter filtering 🧵

Day 16 of #30DaysOfSQL — INNER JOIN 🤝 INNER JOIN = return rows that exist in both tables. 🧵

Day 10 of #30DaysOfSQL 🚀 Today I learned Aggregate Functions (they summarize data 📊):

Day 26 of #30DaysOfSQL CTEs just made SQL make sense Today I learned how Common Table Expressions (CTEs) break complex logic into simple, readable steps. Instead of stuffing everything into one massive query, a CTE lets you think in layers.

Day 14 of #30DaysOfSQL Learning CASE WHEN → SQL’s way of adding if/else logic inside queries. 🧵

Day 15 of #30DaysOfSQL 🚀 Today I learned about Keys → the backbone of relational databases.🧵

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 17 of #30DaysOfSQL LEFT JOIN vs RIGHT JOIN What if you want all rows from one table (even without a match)?🧵

🔷Day 9 of #SQLwithFunmi: I harnessed LIKE, IN, and BETWEEN to filter data with ease. Retrieved corps members by email, state, age, and name patterns. LIKE with wildcards (%) and IN for multiple values were total lifesavers! Now, querying data feels like a breeze! #30DaysOfSQL

Day 14 of #30DaysOfSQL Today I learned Subqueries → queries inside queries. Think of it as: “Find X, then use X to find Y.”🧵

Day 10 of #SQLwithFunmi! 🔷 Mastered logical reasoning with SQL. Retrieved corps members based on complex conditions like age range, preferred state vs. origin state, and missing contact details. Discovered the importance of using IS NULL for missing values. 💻 #30DaysOfSQL #SQLS

Catching up on Day 7 of #SQLwithFunmi! 🔷 Mastered aggregation with MIN, MAX, COUNT, GROUP BY, and ORDER BY. Found youngest/oldest corps members and counted members by institution state. Powerful techniques for data analysis! 💻 #30DaysOfSQL #SQLSkills #DataAnalytics

Day 8 of #SQLwithFunmi! 🔷 Mastered DISTINCT, HAVING, and LIMIT. Retrieved unique states, institutions, and courses. Filtered grouped results and displayed top records. 💻 #30DaysOfSQL #SQLSkills #DataAnalytics

Day 12 of My #30DaysOfSQL Challenge SQL isn’t just about numbers it’s also about time. Today, I explored Date & Time functions that help analyze patterns across days, months, and years. 🧵

Day 27 of my #30DaysOfSQL Stored Procedures vs Functions, finally making sense. Today I focused on SQL Functions, and they were confusing at first. The breakthrough came when I understood this simple idea: Stored procedures PERFORM tasks. Functions RETURN results.