#30daysofsql search results

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.

iam_AruCole's tweet image. 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.
iam_AruCole's tweet image. 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.
iam_AruCole's tweet image. 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 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.

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

iam_AruCole's tweet image. Day 14 of #30DaysOfSQL 

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

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

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

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

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

iam_AruCole's tweet image. Day 18 of #30DaysOfSQL — FULL JOIN & CROSS JOIN (MySQL)

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

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

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

MySQL doesn’t support FULL JOIN directly. But here’s how to handle it 🧵

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.

iam_AruCole's tweet image. 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.
iam_AruCole's tweet image. 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.
iam_AruCole's tweet image. 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.
iam_AruCole's tweet image. 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 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 🧵

iam_AruCole's tweet image. 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 🧵
iam_AruCole's tweet image. 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 🧵
iam_AruCole's tweet image. 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 🧵
iam_AruCole's tweet image. 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 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

Ab_Pelz's tweet image. 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 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

iam_AruCole's tweet image. 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
iam_AruCole's tweet image. 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

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.

vaibhavk1874's tweet image. 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.

Last week of #30DaysofSQL with @nairobi_ai .Data storage on Cloud using AWS.

adindArthur's tweet image. Last week of #30DaysofSQL with @nairobi_ai .Data storage on Cloud using AWS.

Currently attending the #30DaysofSQL with @nairobi_ai. Eat. Sleep. Code. Repeat

adindArthur's tweet image. Currently attending the #30DaysofSQL with @nairobi_ai. Eat. Sleep. Code. Repeat

Another Monday, another day ticked off the #30DaysofSQL calendar with @nairobi_ai

adindArthur's tweet image. Another Monday, another day ticked off the #30DaysofSQL calendar with @nairobi_ai

Day 16 Today, I learnt about Common Tables Expression. CTEs act as virtual tables (with records and columns) that are created during query execution, used by the query, and deleted after the query executes. #Day16 #30DaysOfSQL #CTE #Data

Favboladale's tweet image. Day 16

Today, I learnt about Common Tables Expression. CTEs act as virtual tables (with records and columns) that are created during query execution, used by the query, and deleted after the query executes. 

#Day16 #30DaysOfSQL #CTE #Data

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

Stacierealm's tweet image. 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 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

gkgikungu's tweet image. 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

🔷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

MightyAbdboss's tweet image. 🔷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
MightyAbdboss's tweet image. 🔷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
MightyAbdboss's tweet image. 🔷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
MightyAbdboss's tweet image. 🔷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

MightyAbdboss's tweet image. 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
MightyAbdboss's tweet image. 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
MightyAbdboss's tweet image. 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 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

gkgikungu's tweet image. 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

My #30DaysofSQL started today, I may be behind but as an #ALX_DS student #DoHardThings is my motto. @explore_ai @alx_africa

gkgikungu's tweet image. My #30DaysofSQL started today, I may be behind but as an #ALX_DS student #DoHardThings is my motto. 
@explore_ai 
@alx_africa

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