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A simple way to remember which I use for the example given above: RANK -> 1224 (skip) DENSE_RANK-> 1223 (no skip) ROW_NUMBER -> 1234 (sequence) Hope it helps you as well :)

SQL Interview Questions with detailed answers: 5️⃣ Difference between RANK(), DENSE_RANK(), and ROW_NUMBER() 1️⃣ RANK() assigns a rank to each row based on the specified order. If two rows have the same value, they get the same rank, but the next rank is skipped. Example: If two employees have the same salary and rank as 2, the next rank will be 4 (skipping 3).

    
        SELECT employee_id, salary, 
       RANK() OVER (ORDER BY salary DESC) AS rank
FROM employees;{}
    

2️⃣ DENSE_RANK() is similar to RANK(), but it does not skip ranks when there are ties. Example: If two employees share rank 2, the next rank will be 3 instead of skipping it.

    
        SELECT employee_id, salary, 
       DENSE_RANK() OVER (ORDER BY salary DESC) AS dense_rank
FROM employees;{}
    

3️⃣ ROW_NUMBER() assigns a unique number to each row, even if the values are the same. No ties occur, and every row gets a unique sequential number.

    
        SELECT employee_id, salary, 
       ROW_NUMBER() OVER (ORDER BY salary DESC) AS row_num
FROM employees;{}
    

⬇️ Key Differences: RANK() skips numbers when there are duplicates. DENSE_RANK() does not skip numbers and assigns the next rank sequentially. ROW_NUMBER() does not allow ties and gives every row a unique number. Top 20 SQL Interview Questions Like this post if you want me to continue this SQL Interview Series♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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SQL Interview Questions with detailed answers: 4️⃣ How do you remove duplicate rows from a table? To remove duplicate rows, you can use the DISTINCT keyword in a SELECT query. Example:

    
        SELECT DISTINCT column_name FROM table_name; {}
    

Explanation: DISTINCT will return only unique rows for the specified column(s). It compares all columns in the query and removes duplicates. For example, if you have a table of employees and some rows are repeated, using DISTINCT will only return unique employees. Example with multiple columns:

    
        SELECT DISTINCT first_name, last_name FROM employees; {}
    

This will return only unique combinations of first and last names. Top 20 SQL Interview Questions Like this post if you want me to continue this SQL Interview Series♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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Guys, please check out my SQL tutorial if you're getting this wrong! 👇 https://t.me/sqlspecialist/567 For the next few days, I'll be posting basic data analytics questions to ensure all my subscribers understand the essential concepts. Once I see 80%+ correct answers, we'll move on to more advanced polls and quizzes! Hope you all succeed one day :)

SQL Interview Questions with detailed answers: 3️⃣ What is the difference between HAVING and WHERE? WHERE: It is used to filter records before any grouping occurs. It operates on individual rows in the table. HAVING: It is used to filter records after the grouping operation. It works on aggregated data (e.g., data created using GROUP BY). Example:

    
        -- Using WHERE to filter rows before grouping 
SELECT department_id, AVG(salary) AS avg_salary FROM employees WHERE salary > 50000 GROUP BY department_id; 

-- Using HAVING to filter groups after aggregation 
SELECT department_id, AVG(salary) AS avg_salary FROM employees GROUP BY department_id HAVING AVG(salary) > 60000; {}
    

Explanation: WHERE filters rows where the salary is greater than 50,000 before grouping by department. HAVING filters departments where the average salary is greater than 60,000 after grouping. Key difference: WHERE filters individual rows. HAVING filters groups after aggregation. Like this post if you want me to continue this SQL Interview Series♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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        SELECT Region, SUM(Sales) AS Total_Sales, AVG(Sales) AS Avg_Sales
FROM Sales
GROUP BY Region;{}
    

📌 Step 4: Visualize the Insights Once you've analyzed the data, create visualizations to make the insights clear and actionable: 💹 Use line charts for trends over time. 📊 Use bar charts to compare different segments (regions, products, etc.). 🗺 Use heatmaps for geographical analysis. 💡 Tip: Keep your visualizations simple and focused on the key insights. 📌 Step 5: Provide Recommendations Finally, based on your analysis, provide actionable recommendations to the business. For example: “Focus promotions on Region X, where sales are consistently lower than other regions.” “Increase marketing spend for the high-performing products.” Free Resources for business analysts 👇👇 https://t.me/analystcommunity Share with credits: https://t.me/sqlspecialist Hope it helps :)

SQL Interview Questions with detailed answers: 2️⃣ How does GROUP BY work, and why do we use it? GROUP BY is used to arrange identical data into groups, often for performing aggregation functions (like COUNT, SUM, AVG, etc.) on each group. It's typically used with aggregate functions to summarize data. Example: Consider a sales table:

    
        SELECT department_id, SUM(salary) AS total_salary FROM employees GROUP BY department_id; {}
    

Explanation: GROUP BY department_id: This groups all rows in the employees table by their department. SUM(salary): This calculates the total salary for each department. The result will show the department_id along with the corresponding total salary. Why use GROUP BY? It allows you to analyze data at different levels of granularity (e.g., department, region) by summarizing data in a meaningful way. Like this post if you want me to continue this SQL Interview Series♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)