#30daysofsql resultados da pesquisa
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 18 of #30DaysOfSQL — FULL JOIN & CROSS JOIN (MySQL) MySQL doesn’t support FULL JOIN directly. But here’s how to handle it 🧵
Day 15 of SQL May Challenge. I worked on the Adventure work data set from Kaggle, exported it to SQL, used my JOIN to combine the data (because they were on different tables). Then, I exported it to POWER BI, wrote 1 or 2 DAX functions, designed this dashboard. #30daysofSQL
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 🧵
Day 14 of #30DaysOfSQL Today I learned Subqueries → queries inside queries. Think of it as: “Find X, then use X to find Y.”🧵
I started #30daysofSQL today. Day 1 of SQL Topics Covered: _ Overview of SQL _ History of SQL _ Basic Commands in SQL _ Advantage of SQL _ SQL vs NOSQL difference 📌What is SQL? Sql is a standard database Language used to access and manipulate data in databases.
Day 11 Today, I learnt how to manage tables using constraints in SQL (Not Null, Default, Check, Unique) In simple terms, constraints help maintain consistent, valid, and high-quality data, which is crucial for robust database management and meaningful data analysis #30DaysOfSQL
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+ 💪🧵
🔷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 11 of #30DaysofSQL was all about harnessing the power of SQL in notebooks! 📊 From querying data with precision to mastering numeric functions and aggregations, the journey to becoming a SQL pro is getting more exciting. Let's crunch some numbers! 💻 #DoHardThings @alx_kenya
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 4 of #SQLwithFunmi! 🔷 Mastered COUNT, GROUP BY, and AVERAGE. Retrieved corps members' count by state, preferred state, course, and average age. Levelling up day after day😌💻 #30DaysOfSQL #LearningInPublic #DataAnalytics
Day 10 of #30DaysofSQL has been a rollercoaster! Challenging yet fun sums it up. Anaconda Navigator has opened up endless possibilities. The #DoHardThings challenges are real, but so is the excitement of mastering this powerful tool. 📊 @alx_kenya #DataNerd #NeverStopLearning
🧵 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. 🧵
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 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
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 15 of SQL May Challenge. I worked on the Adventure work data set from Kaggle, exported it to SQL, used my JOIN to combine the data (because they were on different tables). Then, I exported it to POWER BI, wrote 1 or 2 DAX functions, designed this dashboard. #30daysofSQL
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
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 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 🧵
Day 5 of #SQLChallengewithFunmi! 🔷 Mastered filtering with AND & BETWEEN. Retrieved corps members based on age, graduating honors, state of origin, and preferred state. Learned powerful operators for precise queries! 💻 #30DaysOfSQL #LearningInPublic #DataAnalytics
Day 6 of #SQLwithFunmi! 🔷 Today was a lot! despite the busy day and the festivities, I was able to get to code a little. Still on the NYSC database. 💻 #30DaysOfSQL #LearningInPublic #DataAnalytics
Day 17 of #30DaysOfSQL LEFT JOIN vs RIGHT JOIN What if you want all rows from one table (even without a match)?🧵
Day 4 of #SQLwithFunmi! 🔷 Mastered COUNT, GROUP BY, and AVERAGE. Retrieved corps members' count by state, preferred state, course, and average age. Levelling up day after day😌💻 #30DaysOfSQL #LearningInPublic #DataAnalytics
Day 18 of #30DaysOfSQL — FULL JOIN & CROSS JOIN (MySQL) MySQL doesn’t support FULL JOIN directly. But here’s how to handle it 🧵
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