Data Analytics - SQL, Python, Excel, AI & ChatGPT

✅Skills Required to Become a Data Analyst 📊 🧠 ANALYTICAL THINKING 1. Problem Solving 2. Logical Reasoning 3. Pattern Recognition 4. Critical Thinking 5. Decision Making 6. Root Cause Analysis 7. Attention to Detail 8. Business Understanding 📊 DATA HANDLING 1. Data Cleaning 2. Data Transformation 3. Data Validation 4. Handling Missing Values 5. Data Wrangling 6. Data Integration 7. Data Formatting 8. Data Quality Checks 🗄️ SQL SKILLS 1. Writing Queries 2. Joins (INNER, LEFT, RIGHT) 3. Aggregations (SUM, COUNT, AVG) 4. Subqueries 5. CTEs 6. Window Functions 7. Indexing Basics 8. Database Optimization 🐍 PYTHON / R 1. Pandas / dplyr 2. NumPy 3. Data Cleaning Scripts 4. EDA (Exploratory Data Analysis) 5. Visualization Libraries 6. Automation 7. Statistical Analysis 8. Basic Machine Learning 📊 DATA VISUALIZATION 1. Dashboard Creation 2. Chart Selection 3. Storytelling with Data 4. Power BI / Tableau 5. KPI Design 6. Report Building 7. Interactive Visuals 8. Data Presentation 📈 STATISTICS 1. Mean, Median, Mode 2. Probability Basics 3. Hypothesis Testing 4. Correlation 5. Regression 6. Distribution 7. Sampling Techniques 8. A/B Testing 💼 BUSINESS SKILLS 1. Requirement Understanding 2. Stakeholder Communication 3. Business Metrics 4. Domain Knowledge 5. Problem Framing 6. Reporting Insights 7. Decision Support 8. Documentation ⚙️ TOOLS  TECHNOLOGIES 1. Excel 2. SQL Tools (MySQL, PostgreSQL) 3. Power BI / Tableau 4. Python / R 5. Google Sheets 6. Jupyter Notebook 7. Git (Basics) 8. Cloud Basics (AWS / Azure) 💬 Tap ❤️ for more

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🔥 Now, let’s move to the next topic: ✅ CTE (Common Table Expressions) 🧠 1. What is a CTE? A CTE (Common Table Expression) is a temporary result set 👉 defined using WITH 👉 used to simplify complex queries Think like this 👇 👉 “Create a temporary table → use it in your query” ⚡ 2. Basic Syntax

    
        WITH cte_name AS (
    SELECT ...
)
SELECT * FROM cte_name;
{}
    

🎯 3. Simple Example 👉 Get employees with salary > 50k

    
        WITH high_salary AS (
    SELECT * FROM employees
    WHERE salary > 50000
)
SELECT * FROM high_salary;
{}
    

✔ Makes query more readable 🔥 4. CTE with Aggregation 👉 Average salary per department

    
        WITH dept_avg AS (
    SELECT department, AVG(salary) AS avg_salary
    FROM employees
    GROUP BY department
)
SELECT * FROM dept_avg;
{}
    

⚡ 5. CTE vs Subquery CTE -> More readable, Reusable Better for complex queries Subquery -> Hard to read Not reusable 🎯 6. Real Example (Interview Level) 👉 Employees earning above department average

    
        WITH dept_avg AS (
    SELECT department, AVG(salary) AS avg_salary
    FROM employees
    GROUP BY department
)

SELECT e.name, e.salary, e.department
FROM employees e
JOIN dept_avg d
ON e.department = d.department
WHERE e.salary > d.avg_salary;
{}
    

🎯 7. Practice Tasks 1. Create CTE for employees with salary > 40k 2. Find average salary using CTE 3. Get employees above average salary using CTE 4. Count employees per department using CTE 5. Find highest salary per department using CTE 🔥 Here are the solutions for CTE practice tasks ✅ 1. Create CTE for employees with salary > 40k

    
        WITH high_salary AS (
    SELECT * FROM employees
    WHERE salary > 40000
)
SELECT * FROM high_salary;
{}
    

✅ 2. Find average salary using CTE

    
        WITH avg_sal AS (
    SELECT AVG(salary) AS avg_salary FROM employees
)
SELECT * FROM avg_sal;
{}
    

✅ 3. Get employees above average salary using CTE

    
        WITH avg_sal AS (
    SELECT AVG(salary) AS avg_salary FROM employees
)
SELECT e.*
FROM employees e, avg_sal a
WHERE e.salary > a.avg_salary;
{}
    

👉 Alternative (JOIN style):

    
        WITH avg_sal AS (
    SELECT AVG(salary) AS avg_salary FROM employees
)
SELECT e.*
FROM employees e
JOIN avg_sal a
ON e.salary > a.avg_salary;
{}
    

✅ 4. Count employees per department using CTE

    
        WITH dept_count AS (
    SELECT department, COUNT(*) AS total_emp
    FROM employees
    GROUP BY department
)
SELECT * FROM dept_count;
{}
    

✅ 5. Find highest salary per department using CTE

    
        WITH max_sal AS (
    SELECT department, MAX(salary) AS max_salary
    FROM employees
    GROUP BY department
)
SELECT * FROM max_sal;
{}
    

⚡ Mini Challenge 🔥 👉 Find top 2 highest salary employees per department using CTE ⚡ Mini Challenge Solution 🔥

    
        WITH ranked_emp AS (
    SELECT name, department, salary,
           ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rn
    FROM employees
)
SELECT * FROM ranked_emp
WHERE rn <= 2;
{}
    

🔥 Pro Tip: Whenever query looks messy: 👉 Replace subquery with CTE Double Tap ❤️ For More

🔥 Now, let’s move to the next topic: ✅ Window 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