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@Vendetta1313_ Que le van a pedir a una vieja que se comporte como un futbolero de verdad. No han entendido nada.
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Mi balance del Mundial hasta ahora
Europa: la más completa.
Cualidad: organización táctica e intensidad.
Defecto: demasiado rígida y predecible.
Norteamérica y Centroamérica: la más física.
Cualidad: presión alta y transiciones rápidas.
Defecto: le cuesta elaborar juego ante defensas cerradas.
África: la gran revelación.
Cualidad: velocidad, físico y crecimiento táctico.
Defecto: todavía sufre desconexiones y errores de concentración.
Asia: la más disciplinada.
Cualidad: orden táctico e intensidad.
Defecto: menor profundidad de plantilla y menos jerarquía individual.
Suramérica: la más talentosa.
Cualidad: técnica y creatividad individual.
Defecto: menor intensidad colectiva y excesiva dependencia de las figuras.
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Full Name: Hazel Moore
Date of Birth: June 9, 2000
Age: 26 years old
Birthplace: New York, United States
Nationality: American
Ethnicity: Caucasian
Profession: Model
Years Active: 2019–present (approximately 7 years)
Height: 5'7" (170 cm)
Weight: 121 lbs (55 kg)
Body Type: Slim
Hair Color: Brown
Eye Color: Hazel
Known For: Modeling career that began in 2019.



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Most SQL developers can write queries.
Very few understand what happens automatically after data changes.
If you want to learn SQL Triggers, study these concepts:
1). BEFORE Triggers
2).AFTER Triggers
3) INSTEAD OF Triggers
4) Row-Level Triggers
5) Statement-Level Triggers
6) Audit Logging
7) Data Validation
8) Soft Deletes
9) Business Rule Enforcement
10) Trigger Performance
Nested Triggers
Production Best Practices
Master these and you'll understand how enterprise databases automate business logic at scale.
Here's the Advanced SQL Trigger Cheat Sheet 👇

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@periodistan_ Con razón estos homosexuales de mierda no son capaces de ganarle a los simios de Marruecos.
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🔥 Learn how to create Matrix-Chart combinations in Power BI (.pbix included)
🔗 medium.com/microsoft-powe…
Get all our tutorials: powerbi-masterclass.short.gy/power-bi?utm_c…
#powerbi #datafam #dataviz

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📊 Building Interactive Flip-Card KPIs in Power BI: The HTML DAX Technique That Makes Static Cards Obsolete
🔗 medium.com/microsoft-powe…
Get all our tutorials: powerbi-masterclass.short.gy/power-bi?utm_c…
GIF
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WORLD CUP PREDICTIONS: MATCHDAY 1
━━━━━━━━━
🇲🇽 Mexico 2-0 South Africa 🇿🇦 done ✅
🇰🇷 South Korea 2-1 Czechia 🇨🇿 done ✅
🇨🇦 Canada 1-1 Bosnia 🇧🇦
🇺🇸 USA 1-0 Paraguay 🇵🇾
🇶🇦 Qatar 0-2 Switzerland 🇨🇭
🇧🇷 Brazil 1-1 Morocco 🇲🇦
🇭🇹 Haiti 0-3 Scotland 🏴
🇦🇺 Australia 1-2 Turkey 🇹🇷
🇩🇪 Germany 5-0 Curacao 🇨🇼
🇳🇱 Netherlands 2-2 Japan 🇯🇵
🇨🇮 Ivory Coast 0-0 Ecuador 🇪🇨
🇸🇪 Sweden 1-0 Tunisia 🇹🇳
🇪🇸 Spain 6-0 Cape Verde 🇨🇻
🇧🇪 Belgium 1-1 Egypt 🇪🇬
🇸🇦 Saudi Arabia 1-2 Uruguay 🇺🇾
🇮🇷 Iran 1-0 New Zealand 🇳🇿
🇫🇷 France 3-1 Senegal 🇸🇳
🇮🇶 Iraq 1-2 Norway 🇳🇴
🇦🇷 Argentina 2-0 Algeria 🇩🇿
🇦🇹 Austria 2-1 Jordan 🇯🇴
🇵🇹 Portugal 3-0 DR Congo 🇨🇩
🏴 England 2-1 Croatia 🇭🇷
🇬🇭 Ghana 2-0 Panama 🇵🇦
🇺🇿 Uzbekistan 0-2 Colombia

K.A.Y.O.D.E@Dhavidtips
Send me sporty code 🧑💻
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@AndresGuryRod @ABDELAESPRIELLA Por esto es que hace tiempo me da una vergüenza decir que soy de derecha. Porque a todos nos encapsulan con estos tipos en la misma pasta.
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Este es el verdadero estallido social, sin capuchas,ni violencia !!!! Hoy el país es VALIENTE!!! @ABDELAESPRIELLA
Medellín, Colombia 🇨🇴 Español

@DGO_Latam @Malejozaja Arreglalo para todos no solo oara los que escriben
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Lo de DGO es una grosería. Si no tienen cómo responder ante la demanda y la calidad de imagen, no se adueñen de los derechos. @DGO_Latam @DIRECTVLA
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✅ WINDOWS FUNCTIONS
🧠 1. What are Window Functions?
Window functions perform calculations without grouping rows
👉 Difference:
- GROUP BY → reduces rows
- Window Function → keeps all rows + adds extra column
📊 Example Table
name → Amit, Ravi, Neha
department → IT, IT, HR
salary → 60000, 70000, 40000
⚡ 2. Basic Syntax
SELECT column,
FUNCTION() OVER (PARTITION BY column ORDER BY column)
FROM table;
🔥 3. ROW_NUMBER()
Assigns unique rank to each row
SELECT name, department, salary,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rank
FROM employees;
✔ Rank employees within each department
🥇 4. RANK() vs DENSE_RANK()
👉 RANK() (skips numbers)
SELECT name, salary,
RANK() OVER (ORDER BY salary DESC) AS rank
FROM employees;
👉 DENSE_RANK() (no skipping)
SELECT name, salary,
DENSE_RANK() OVER (ORDER BY salary DESC) AS rank
FROM employees;
📊 Visual Difference
If salaries are 100, 90, 90, 80:
- RANK() gives: 1, 2, 2, 4
- DENSE_RANK() gives: 1, 2, 2, 3
⚡ 5. PARTITION BY (Very Important)
👉 Splits data into groups (like GROUP BY but without collapsing rows)
SELECT department, name, salary,
AVG(salary) OVER (PARTITION BY department) AS avg_salary
FROM employees;
✔ Shows avg salary per department for each row
🎯 6. Practice Tasks
1. Rank employees by salary
2. Rank employees within each department
3. Find highest salary per department
4. Add average salary column per department
5. Find second highest salary using window function
✅ Practice Tasks Solution
✅ 1. Rank employees by salary
SELECT name, salary,
ROW_NUMBER() OVER (ORDER BY salary DESC) AS rank
FROM employees;
✅ 2. Rank employees within each department
SELECT name, department, salary,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rank
FROM employees;
✅ 3. Find highest salary per department
SELECT name, department, salary
FROM (
SELECT name, department, salary,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rn
FROM employees
) t
WHERE rn = 1;
✅ 4. Add average salary column per department
SELECT name, department, salary,
AVG(salary) OVER (PARTITION BY department) AS avg_salary
FROM employees;
✅ 5. Find second highest salary using window function
SELECT name, salary
FROM (
SELECT name, salary,
DENSE_RANK() OVER (ORDER BY salary DESC) AS rnk
FROM employees
) t
WHERE rnk = 2;
⚡ Mini Challenge 🔥
👉 Get top 2 highest paid employees in each department
⚡ Mini Challenge Solution 🔥
SELECT name, department, salary
FROM (
SELECT name, department, salary,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rn
FROM employees
) t
WHERE rn <= 2;
🔥 Pro Tip
- Use ROW_NUMBER() → unique ranking
- Use DENSE_RANK() → handle ties
Double Tap ❤️ For More
BOOKMARK THIS
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