๐ ๐ง๐ผ๐ฝ ๐ฑ ๐๐ฅ๐๐ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ง๐ผ ๐๐บ๐ฝ๐ฟ๐ผ๐๐ฒ ๐ฌ๐ผ๐๐ฟ ๐ฆ๐ธ๐ถ๐น๐น๐๐ฒ๐ ๐
These 5 FREE courses that can help you stand out in interviews and job applications! ๐ผโจ
๐ Microsoft Excel
๐ Power BI
๐ซ Python for Data Science
โฐTime Management
๐ฐ Basic Financial Accounting
๐ฏ Invest a few hours today to unlock better career opportunities tomorrow!
๐ ๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ผ๐ฟ ๐๐ฅ๐๐ ๐:-
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๐ Save this post and share it with friends looking to upskill in 2026.
These 5 FREE courses that can help you stand out in interviews and job applications! ๐ผโจ
๐ Microsoft Excel
๐ Power BI
๐ซ Python for Data Science
โฐTime Management
๐ฐ Basic Financial Accounting
๐ฏ Invest a few hours today to unlock better career opportunities tomorrow!
๐ ๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ผ๐ฟ ๐๐ฅ๐๐ ๐:-
https://pdlink.in/4dPjz92
๐ Save this post and share it with friends looking to upskill in 2026.
โค5๐1
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this SQL query.
Find the second most recent order placed by each customer.
Assume the table structure:
orders(order_id, customer_id, order_date)
๐ ๐ฒ: Challenge accepted! ๐ช
SELECT
order_id,
customer_id,
order_date
FROM (
SELECT
order_id,
customer_id,
order_date,
ROW_NUMBER() OVER (
PARTITION BY customer_id
ORDER BY order_date DESC
) AS rn
FROM orders
) ranked
WHERE rn = 2;
๐ก Explanation:
The query assigns a rank to each order based on its order date for every customer.
โข PARTITION BY customer_id creates a separate ranking for each customer
โข ORDER BY order_date DESC ranks the most recent order as 1
โข ROW_NUMBER() ensures each order gets a unique rank
โข The outer query returns only the order with rn = 2, i.e., the second most recent order
This question tests your understanding of:
โ Window Functions (ROW_NUMBER)
โ Ranking Records
โ Partitioning Data
โ Top N per Group
๐ฏ Expected Output Example
Customer ID | Order ID | Order Date
101 | 2056 | 2026-06-15
102 | 2074 | 2026-06-18
Customers with fewer than two orders are automatically excluded.
๐ Alternative Using a Correlated Subquery
SELECT
o1.order_id,
o1.customer_id,
o1.order_date
FROM orders o1
WHERE 1 = (
SELECT COUNT(*)
FROM orders o2
WHERE o2.customer_id = o1.customer_id
AND o2.order_date > o1.order_date
);
This approach counts how many orders are more recent than the current order. If exactly one order is more recent, the current order is the second most recent.
๐ Tip for SQL Job Seekers:
Questions involving the Nth latest or Nth earliest record appear frequently in interviews. Practice solving them using:
โข ROW_NUMBER()
โข RANK()
โข DENSE_RANK()
โข Correlated Subqueries
Understanding when to use each approach is a valuable interview skill.
โค๏ธ React with โค๏ธ for more interview challenges!
You have 2 minutes to solve this SQL query.
Find the second most recent order placed by each customer.
Assume the table structure:
orders(order_id, customer_id, order_date)
๐ ๐ฒ: Challenge accepted! ๐ช
SELECT
order_id,
customer_id,
order_date
FROM (
SELECT
order_id,
customer_id,
order_date,
ROW_NUMBER() OVER (
PARTITION BY customer_id
ORDER BY order_date DESC
) AS rn
FROM orders
) ranked
WHERE rn = 2;
๐ก Explanation:
The query assigns a rank to each order based on its order date for every customer.
โข PARTITION BY customer_id creates a separate ranking for each customer
โข ORDER BY order_date DESC ranks the most recent order as 1
โข ROW_NUMBER() ensures each order gets a unique rank
โข The outer query returns only the order with rn = 2, i.e., the second most recent order
This question tests your understanding of:
โ Window Functions (ROW_NUMBER)
โ Ranking Records
โ Partitioning Data
โ Top N per Group
๐ฏ Expected Output Example
Customer ID | Order ID | Order Date
101 | 2056 | 2026-06-15
102 | 2074 | 2026-06-18
Customers with fewer than two orders are automatically excluded.
๐ Alternative Using a Correlated Subquery
SELECT
o1.order_id,
o1.customer_id,
o1.order_date
FROM orders o1
WHERE 1 = (
SELECT COUNT(*)
FROM orders o2
WHERE o2.customer_id = o1.customer_id
AND o2.order_date > o1.order_date
);
This approach counts how many orders are more recent than the current order. If exactly one order is more recent, the current order is the second most recent.
๐ Tip for SQL Job Seekers:
Questions involving the Nth latest or Nth earliest record appear frequently in interviews. Practice solving them using:
โข ROW_NUMBER()
โข RANK()
โข DENSE_RANK()
โข Correlated Subqueries
Understanding when to use each approach is a valuable interview skill.
โค๏ธ React with โค๏ธ for more interview challenges!
โค4๐3
๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
โ 100% FREE learning opportunities
โ Great for students, freshers, and beginners
โ Help you build a stronger resume with recognized names like Cisco, Google, and Microsoft
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๐ ๐๐ป๐ฟ๐ผ๐น๐น ๐๐ผ๐ฟ ๐๐ฅ๐๐๐:
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๐ Start learning today. Build your analytics foundation. Earn free certifications. Move one step closer to your Data Analyst career.
โ 100% FREE learning opportunities
โ Great for students, freshers, and beginners
โ Help you build a stronger resume with recognized names like Cisco, Google, and Microsoft
โ Useful for analytics internships, off-campus drives, and fresher hiring
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๐ Start learning today. Build your analytics foundation. Earn free certifications. Move one step closer to your Data Analyst career.
โค3
If you are interested to learn SQL for data analytics purpose and clear the interviews, just cover the following topics
1)Install MYSQL workbench
2) Select
3) From
4) where
5) group by
6) having
7) limit
8) Joins (Left, right , inner, self, cross)
9) Aggregate function ( Sum, Max, Min , Avg)
9) windows function ( row num, rank, dense rank, lead, lag, Sum () over)
10)Case
11) Like
12) Sub queries
13) CTE
14) Replace CTE with temp tables
15) Methods to optimize Sql queries
16) Solve problems and case studies at Ankit Bansal youtube channel
Trick: Just copy each term and paste on youtube and watch any 10 to 15 minute on each topic and practise it while learning , By doing this , you get the basics understanding
17) Now time to go on youtube and search data analysis end to end project using sql
18) Watch them and practise them end to end.
17) learn integration with power bi
In this way , you will not only memorize the concepts but also learn how to implement them in your current working and projects and will be able to defend it in your interviews as well.
1)Install MYSQL workbench
2) Select
3) From
4) where
5) group by
6) having
7) limit
8) Joins (Left, right , inner, self, cross)
9) Aggregate function ( Sum, Max, Min , Avg)
9) windows function ( row num, rank, dense rank, lead, lag, Sum () over)
10)Case
11) Like
12) Sub queries
13) CTE
14) Replace CTE with temp tables
15) Methods to optimize Sql queries
16) Solve problems and case studies at Ankit Bansal youtube channel
Trick: Just copy each term and paste on youtube and watch any 10 to 15 minute on each topic and practise it while learning , By doing this , you get the basics understanding
17) Now time to go on youtube and search data analysis end to end project using sql
18) Watch them and practise them end to end.
17) learn integration with power bi
In this way , you will not only memorize the concepts but also learn how to implement them in your current working and projects and will be able to defend it in your interviews as well.
โค12๐4
๐๐ฅ๐๐ ๐ฉ๐ถ๐ฟ๐๐๐ฎ๐น ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ฒ ๐๐ป๐๐ฒ๐ฟ๐ป๐๐ต๐ถ๐ฝ๐ | ๐๐ผ๐ผ๐๐ ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ฒ๐๐๐บ๐ฒ๐
These FREE virtual certificate internships can help you build practical skills, industry exposure, and resume value from top companies and global platforms โ all from home.
๐ซPerfect for students, freshers, and career starters
- PwC Power BI Virtual Internship
- British Airways Data Science Virtual Internship
- Quantium Data Analytics Virtual Internship
๐ ๐๐ป๐ฟ๐ผ๐น๐น ๐๐ผ๐ฟ ๐๐ฅ๐๐๐:
https://pdlink.in/44PEjcL
๐ Start learning today. Build experience. Collect certificates. Make your resume stronger.
These FREE virtual certificate internships can help you build practical skills, industry exposure, and resume value from top companies and global platforms โ all from home.
๐ซPerfect for students, freshers, and career starters
- PwC Power BI Virtual Internship
- British Airways Data Science Virtual Internship
- Quantium Data Analytics Virtual Internship
๐ ๐๐ป๐ฟ๐ผ๐น๐น ๐๐ผ๐ฟ ๐๐ฅ๐๐๐:
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๐ Start learning today. Build experience. Collect certificates. Make your resume stronger.
โค2
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this SQL query.
Find employees whose salary is higher than the average salary of all other departments (excluding their own department).
Assume the table structure:
employees(employee_id, employee_name, department, salary)
๐ ๐ฒ: Challenge accepted! ๐ช
SELECT
employee_id,
employee_name,
department,
salary
FROM employees e1
WHERE salary > (
SELECT AVG(salary)
FROM employees e2
WHERE e2.department <> e1.department
);
๐ก Explanation:
This query compares each employee's salary against the average salary of all employees outside their own department.
โข The outer query processes each employee.
โข The correlated subquery calculates the average salary of employees in all other departments.
โข Employees whose salary exceeds that average are returned.
This question tests your understanding of:
โ Correlated Subqueries
โ Aggregate Functions (AVG)
โ Conditional Filtering
โ Cross-group Comparisons
๐ฏ Expected Output Example
Employee: John | Department: IT | Salary: 95,000
Employee: Sarah | Department: HR | Salary: 82,000
๐ Alternative Using Common Table Expressions (CTEs)
WITH dept_avg AS (
SELECT
department,
AVG(salary) AS avg_salary
FROM employees
GROUP BY department
)
SELECT
e.employee_id,
e.employee_name,
e.department,
e.salary
FROM employees e
WHERE e.salary > (
SELECT AVG(avg_salary)
FROM dept_avg d
WHERE d.department <> e.department
);
This version first computes department-level averages and then compares each employee's salary with the average of the other departments' averages.
๐ Tip for SQL Job Seekers:
Interviewers often ask questions that compare data within a group versus outside a group. These problems test your understanding of correlated subqueries and aggregate calculations across multiple levels.
โค๏ธ React with โค๏ธ for more SQL interview challenges!
You have 2 minutes to solve this SQL query.
Find employees whose salary is higher than the average salary of all other departments (excluding their own department).
Assume the table structure:
employees(employee_id, employee_name, department, salary)
๐ ๐ฒ: Challenge accepted! ๐ช
SELECT
employee_id,
employee_name,
department,
salary
FROM employees e1
WHERE salary > (
SELECT AVG(salary)
FROM employees e2
WHERE e2.department <> e1.department
);
๐ก Explanation:
This query compares each employee's salary against the average salary of all employees outside their own department.
โข The outer query processes each employee.
โข The correlated subquery calculates the average salary of employees in all other departments.
โข Employees whose salary exceeds that average are returned.
This question tests your understanding of:
โ Correlated Subqueries
โ Aggregate Functions (AVG)
โ Conditional Filtering
โ Cross-group Comparisons
๐ฏ Expected Output Example
Employee: John | Department: IT | Salary: 95,000
Employee: Sarah | Department: HR | Salary: 82,000
๐ Alternative Using Common Table Expressions (CTEs)
WITH dept_avg AS (
SELECT
department,
AVG(salary) AS avg_salary
FROM employees
GROUP BY department
)
SELECT
e.employee_id,
e.employee_name,
e.department,
e.salary
FROM employees e
WHERE e.salary > (
SELECT AVG(avg_salary)
FROM dept_avg d
WHERE d.department <> e.department
);
This version first computes department-level averages and then compares each employee's salary with the average of the other departments' averages.
๐ Tip for SQL Job Seekers:
Interviewers often ask questions that compare data within a group versus outside a group. These problems test your understanding of correlated subqueries and aggregate calculations across multiple levels.
โค๏ธ React with โค๏ธ for more SQL interview challenges!
1โค10
GigaChat 3.5 Ultra Publicly Released โ The New Generation of the Flagship Model
Whatโs inside:
๐ A proprietary hybrid MLA + Gated DeltaNet architecture with a dedicated stabilization framework, without which this hybrid setup would not train reliably at this scale;
๐ Gated Attention: the model can locally down-weight overly strong signals from the attention layer;
๐ GatedNorm: normalization with an explicit gate that controls signal magnitude across features;
๐ Approximately 4x lower KV cache per token: with the same memory budget, the model can support 2.14x longer context and deliver a 20% throughput increase under load;
๐ Two MTP heads, enabling up to 2.2x faster generation;
๐ FP8 across all training stages with no quality degradation compared with bf16, enabled by custom Triton and CUDA kernels;
๐ A new online RL stage after SFT and DPO.
Results:
๐ GigaChat-3.5-Ultra-Base outperforms DeepSeek V3.2 Exp Base and DeepSeek V4 Flash Base on average across a set of general, math, and code benchmarks:
๐ GigaChat-3.5-Ultra-Instruct is comparable to DeepSeek V3.2 in terms of average score, despite having half the size;
๐ According to the MiniMax-M2.7 LLM judge, the average win rate against GigaChat 3.1 Ultra is 75.9%, and against GPT-5 is 68.7%.
โก๏ธ HuggingFace
The GigaChat team has released GigaChat 3.5 Ultra as open sourceโa new 432B model under the MIT license. This is the first open-source hybrid of GatedDeltaNet and MLA scaled to hundreds of billions of parameters, featuring a proprietary training recipe we refined through more than 1,500 experiments. The model has grown in terms of code, mathematics, agent scenarios, and application domainsโyet itโs 40% smaller than GigaChat 3.1 Ultra.
Whatโs inside:
Results:
The entire stack โ data (our own LLM-filtered Common Crawl, 600+ programming languages in the code), architecture, training methodology, and infrastructure โ was built end-to-end by GigaChat team.
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โค4๐1
Scenario based Interview Questions & Answers for Data Analyst
1. Scenario: You are working on a SQL database that stores customer information. The database has a table called "Orders" that contains order details. Your task is to write a SQL query to retrieve the total number of orders placed by each customer.
Question:
- Write a SQL query to find the total number of orders placed by each customer.
Expected Answer:
SELECT CustomerID, COUNT(*) AS TotalOrders
FROM Orders
GROUP BY CustomerID;
2. Scenario: You are working on a SQL database that stores employee information. The database has a table called "Employees" that contains employee details. Your task is to write a SQL query to retrieve the names of all employees who have been with the company for more than 5 years.
Question:
- Write a SQL query to find the names of employees who have been with the company for more than 5 years.
Expected Answer:
SELECT Name
FROM Employees
WHERE DATEDIFF(year, HireDate, GETDATE()) > 5;
Power BI Scenario-Based Questions
1. Scenario: You have been given a dataset in Power BI that contains sales data for a company. Your task is to create a report that shows the total sales by product category and region.
Expected Answer:
- Load the dataset into Power BI.
- Create relationships if necessary.
- Use the "Fields" pane to select the necessary fields (Product Category, Region, Sales).
- Drag these fields into the "Values" area of a new visualization (e.g., a table or bar chart).
- Use the "Filters" pane to filter data as needed.
- Format the visualization to enhance clarity and readability.
2. Scenario: You have been asked to create a Power BI dashboard that displays real-time stock prices for a set of companies. The stock prices are available through an API.
Expected Answer:
- Use Power BI Desktop to connect to the API.
- Go to "Get Data" > "Web" and enter the API URL.
- Configure the data refresh settings to ensure real-time updates (e.g., setting up a scheduled refresh or using DirectQuery if supported).
- Create visualizations using the imported data.
- Publish the report to the Power BI service and set up a data gateway if needed for continuous refresh.
3. Scenario: You have been given a Power BI report that contains multiple visualizations. The report is taking a long time to load and is impacting the performance of the application.
Expected Answer:
- Analyze the current performance using Performance Analyzer.
- Optimize data model by reducing the number of columns and rows, and removing unnecessary calculations.
- Use aggregated tables to pre-compute results.
- Simplify DAX calculations.
- Optimize visualizations by reducing the number of visuals per page and avoiding complex custom visuals.
- Ensure proper indexing on the data source.
Free SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like if you need more similar content
Hope it helps :)
1. Scenario: You are working on a SQL database that stores customer information. The database has a table called "Orders" that contains order details. Your task is to write a SQL query to retrieve the total number of orders placed by each customer.
Question:
- Write a SQL query to find the total number of orders placed by each customer.
Expected Answer:
SELECT CustomerID, COUNT(*) AS TotalOrders
FROM Orders
GROUP BY CustomerID;
2. Scenario: You are working on a SQL database that stores employee information. The database has a table called "Employees" that contains employee details. Your task is to write a SQL query to retrieve the names of all employees who have been with the company for more than 5 years.
Question:
- Write a SQL query to find the names of employees who have been with the company for more than 5 years.
Expected Answer:
SELECT Name
FROM Employees
WHERE DATEDIFF(year, HireDate, GETDATE()) > 5;
Power BI Scenario-Based Questions
1. Scenario: You have been given a dataset in Power BI that contains sales data for a company. Your task is to create a report that shows the total sales by product category and region.
Expected Answer:
- Load the dataset into Power BI.
- Create relationships if necessary.
- Use the "Fields" pane to select the necessary fields (Product Category, Region, Sales).
- Drag these fields into the "Values" area of a new visualization (e.g., a table or bar chart).
- Use the "Filters" pane to filter data as needed.
- Format the visualization to enhance clarity and readability.
2. Scenario: You have been asked to create a Power BI dashboard that displays real-time stock prices for a set of companies. The stock prices are available through an API.
Expected Answer:
- Use Power BI Desktop to connect to the API.
- Go to "Get Data" > "Web" and enter the API URL.
- Configure the data refresh settings to ensure real-time updates (e.g., setting up a scheduled refresh or using DirectQuery if supported).
- Create visualizations using the imported data.
- Publish the report to the Power BI service and set up a data gateway if needed for continuous refresh.
3. Scenario: You have been given a Power BI report that contains multiple visualizations. The report is taking a long time to load and is impacting the performance of the application.
Expected Answer:
- Analyze the current performance using Performance Analyzer.
- Optimize data model by reducing the number of columns and rows, and removing unnecessary calculations.
- Use aggregated tables to pre-compute results.
- Simplify DAX calculations.
- Optimize visualizations by reducing the number of visuals per page and avoiding complex custom visuals.
- Ensure proper indexing on the data source.
Free SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like if you need more similar content
Hope it helps :)
โค9
๐๐ ๐ถ๐ป ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐ ๐ ๐ฎ๐ป๐ฎ๐ด๐ฒ๐บ๐ฒ๐ป๐ ๐๐ฅ๐๐ ๐ข๐ป๐น๐ถ๐ป๐ฒ ๐ ๐ฎ๐๐๐ฒ๐ฟ๐ฐ๐น๐ฎ๐๐ ๐
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โค3๐1
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this SQL query.
Q: Find the customer(s) who placed orders in every month of the year 2025.
Assume the table structure:
orders(order_id, customer_id, order_date)
๐ ๐ฒ: Challenge accepted! ๐ช
๐ก Explanation:
This query identifies customers who placed at least one order in every month of 2025.
โข
โข
โข
โข
This question tests your understanding of:
โ Date Functions (YEAR, MONTH)
โ GROUP BY
โ HAVING
โ COUNT(DISTINCT)
๐ฏ Expected Output Example
| Customer ID |
|-------------|
| 101 |
| 205 |
These customers placed at least one order in every month of 2025.
๐ Alternative (Database-Agnostic SQL)
This version works with databases like PostgreSQL and Oracle that support the
๐ Tip for SQL Job Seekers:
Whenever you see interview questions containing phrases like:
"Every month" / "Every quarter" / "Every year" / "Every category"
Think of
โค๏ธ React with โค๏ธ for more interview challenges!
You have 2 minutes to solve this SQL query.
Q: Find the customer(s) who placed orders in every month of the year 2025.
Assume the table structure:
orders(order_id, customer_id, order_date)
๐ ๐ฒ: Challenge accepted! ๐ช
SELECT
customer_id
FROM orders
WHERE YEAR(order_date) = 2025
GROUP BY customer_id
HAVING COUNT(DISTINCT MONTH(order_date)) = 12;
๐ก Explanation:
This query identifies customers who placed at least one order in every month of 2025.
โข
WHERE YEAR(order_date) = 2025 filters orders from the year 2025โข
GROUP BY customer_id groups all orders by customerโข
COUNT(DISTINCT MONTH(order_date)) counts the unique months in which each customer placed an orderโข
HAVING ... = 12 ensures the customer has orders in all 12 monthsThis question tests your understanding of:
โ Date Functions (YEAR, MONTH)
โ GROUP BY
โ HAVING
โ COUNT(DISTINCT)
๐ฏ Expected Output Example
| Customer ID |
|-------------|
| 101 |
| 205 |
These customers placed at least one order in every month of 2025.
๐ Alternative (Database-Agnostic SQL)
SELECT
customer_id
FROM orders
WHERE EXTRACT(YEAR FROM order_date) = 2025
GROUP BY customer_id
HAVING COUNT(DISTINCT EXTRACT(MONTH FROM order_date)) = 12;
This version works with databases like PostgreSQL and Oracle that support the
EXTRACT() function.๐ Tip for SQL Job Seekers:
Whenever you see interview questions containing phrases like:
"Every month" / "Every quarter" / "Every year" / "Every category"
Think of
COUNT(DISTINCT ...) combined with GROUP BY and HAVING. This is a very common SQL interview pattern.โค๏ธ React with โค๏ธ for more interview challenges!
โค15
๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐๐
Offers a wide range of free learning resources through Microsoft Learn, helping students, freshers, and professionals build job-ready skills at their own pace.
โ 100% FREE self-paced learning modules
โ Official learning platform from Microsoft
๐ ๐๐ป๐ฟ๐ผ๐น๐น ๐๐ผ๐ฟ ๐๐ฅ๐๐๐:
https://pdlink.in/4paqRJS
Explore Microsoftโs free resources. Build in-demand skills and make your profile stronger.
Offers a wide range of free learning resources through Microsoft Learn, helping students, freshers, and professionals build job-ready skills at their own pace.
โ 100% FREE self-paced learning modules
โ Official learning platform from Microsoft
๐ ๐๐ป๐ฟ๐ผ๐น๐น ๐๐ผ๐ฟ ๐๐ฅ๐๐๐:
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Explore Microsoftโs free resources. Build in-demand skills and make your profile stronger.
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this SQL query.
Q: Find the employee(s) who received the highest salary increment compared to their previous salary.
Assume the table structure:
salary_history(employee_id, salary, effective_date)
๐ ๐ฒ: Challenge accepted! ๐ช
๐ก Explanation:
This query calculates each employee's salary increment and then finds the highest increment across all employees.
โข LAG(salary) retrieves the employee's previous salary
โข The difference between the current and previous salary gives the increment
โข DENSE_RANK() ranks increments from highest to lowest
โข The outer query returns all employees tied for the highest salary increment
This question tests your understanding of:
โ LAG() Window Function
โ Common Table Expressions (CTEs)
โ DENSE_RANK()
โ Time-Series Data Analysis
๐ฏ Expected Output Example
Employee ID | Salary Increment
101 | 20,000
205 | 20,000
Both employees received the largest salary increase.
๐ Why Interviewers Ask This?
This is a classic window function interview question. It evaluates your ability to compare a row with its previous rowโa common requirement in payroll, finance, and audit systems.
๐ Tip for SQL Job Seekers:
Master these analytical window functions:
LAG() / LEAD() / FIRST_VALUE() / LAST_VALUE() / NTILE()
These functions are frequently tested in product-based companies and data-focused interviews because they simplify complex row-by-row comparisons.
โค๏ธ React with โค๏ธ for more interview challenges!
You have 2 minutes to solve this SQL query.
Q: Find the employee(s) who received the highest salary increment compared to their previous salary.
Assume the table structure:
salary_history(employee_id, salary, effective_date)
๐ ๐ฒ: Challenge accepted! ๐ช
WITH salary_changes AS (
SELECT
employee_id,
salary,
effective_date,
salary - LAG(salary) OVER (
PARTITION BY employee_id
ORDER BY effective_date
) AS salary_increment
FROM salary_history
)
SELECT
employee_id,
salary_increment
FROM (
SELECT
employee_id,
salary_increment,
DENSE_RANK() OVER (
ORDER BY salary_increment DESC
) AS rnk
FROM salary_changes
WHERE salary_increment IS NOT NULL
) ranked
WHERE rnk = 1;
๐ก Explanation:
This query calculates each employee's salary increment and then finds the highest increment across all employees.
โข LAG(salary) retrieves the employee's previous salary
โข The difference between the current and previous salary gives the increment
โข DENSE_RANK() ranks increments from highest to lowest
โข The outer query returns all employees tied for the highest salary increment
This question tests your understanding of:
โ LAG() Window Function
โ Common Table Expressions (CTEs)
โ DENSE_RANK()
โ Time-Series Data Analysis
๐ฏ Expected Output Example
Employee ID | Salary Increment
101 | 20,000
205 | 20,000
Both employees received the largest salary increase.
๐ Why Interviewers Ask This?
This is a classic window function interview question. It evaluates your ability to compare a row with its previous rowโa common requirement in payroll, finance, and audit systems.
๐ Tip for SQL Job Seekers:
Master these analytical window functions:
LAG() / LEAD() / FIRST_VALUE() / LAST_VALUE() / NTILE()
These functions are frequently tested in product-based companies and data-focused interviews because they simplify complex row-by-row comparisons.
โค๏ธ React with โค๏ธ for more interview challenges!
โค13
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๐ Start learning today. Build in-demand skills. Position yourself for better opportunities and bigger career growth.
This guide highlights 3 powerful skills that are opening doors to high-paying roles across tech and business .๐
Perfect For
๐จโ๐ Students
๐ผ Freshers
๐ Job seekers trying to improve employability
๐ Anyone who wants to build a future-proof career with better salary potential
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๐ 1. Microsoft Excel
Used For:
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Formulas & Functions
Pivot Tables
Dashboards
๐๏ธ 2. SQL
Used For:
Querying Databases
Data Extraction
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Reporting
๐ 3. Power BI
Used For:
Interactive Dashboards
Data Visualization
Business Intelligence
KPI Reporting
๐ 4. Tableau
Used For:
Data Visualization
Dashboard Creation
Business Reporting
๐ 5. Python
Used For:
Data Cleaning
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Data Visualization
๐ 6. Power Query
Used For:
Data Transformation
Data Cleaning
ETL Processes
๐ Double Tap โค๏ธ For More
If you're starting your journey as a Data Analyst, focus on these essential tools first. These are the tools most commonly required in job descriptions and used in day-to-day work.
๐ 1. Microsoft Excel
Used For:
Data Cleaning
Formulas & Functions
Pivot Tables
Dashboards
๐๏ธ 2. SQL
Used For:
Querying Databases
Data Extraction
Data Analysis
Reporting
๐ 3. Power BI
Used For:
Interactive Dashboards
Data Visualization
Business Intelligence
KPI Reporting
๐ 4. Tableau
Used For:
Data Visualization
Dashboard Creation
Business Reporting
๐ 5. Python
Used For:
Data Cleaning
Automation
Data Analysis
Data Visualization
๐ 6. Power Query
Used For:
Data Transformation
Data Cleaning
ETL Processes
๐ Double Tap โค๏ธ For More
โค23
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๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this SQL query.
Find the employee(s) who have worked on the highest number of distinct projects.
Assume the table structure: employee_projects(employee_id, project_id)
๐ ๐ฒ: Challenge accepted! ๐ช
๐ก Explanation:
This query counts the number of unique projects each employee has worked on and identifies those with the highest count.
โข COUNT(DISTINCT project_id) counts unique projects for each employee
โข GROUP BY employee_id creates one record per employee
โข DENSE_RANK() ranks employees based on the number of projects
โข The outer query returns all employees tied for the highest number of projects
This question tests your understanding of:
โ COUNT(DISTINCT)
โ GROUP BY
โ Window Functions DENSE_RANK
โ Ranking Aggregated Results
๐ฏ Expected Output Example
Employee ID | Total Projects
101 | 12
205 | 12
Both employees have worked on the highest number of distinct projects.
๐ Alternative Without Window Functions
This solution uses nested subqueries and MAX() instead of window functions.
๐ Tip for SQL Job Seekers:
Many interview questions involve ranking aggregated results, such as:
Highest number of projects, Most orders, Maximum sales, Highest attendance, Most logins
Practice combining GROUP BY with window functions like DENSE_RANK() to solve these efficiently.
โค๏ธ React with โค๏ธ for more interview challenges!
You have 2 minutes to solve this SQL query.
Find the employee(s) who have worked on the highest number of distinct projects.
Assume the table structure: employee_projects(employee_id, project_id)
๐ ๐ฒ: Challenge accepted! ๐ช
SELECT
employee_id,
total_projects
FROM (
SELECT
employee_id,
COUNT(DISTINCT project_id) AS total_projects,
DENSE_RANK() OVER (
ORDER BY COUNT(DISTINCT project_id) DESC
) AS rnk
FROM employee_projects
GROUP BY employee_id
) ranked
WHERE rnk = 1;
๐ก Explanation:
This query counts the number of unique projects each employee has worked on and identifies those with the highest count.
โข COUNT(DISTINCT project_id) counts unique projects for each employee
โข GROUP BY employee_id creates one record per employee
โข DENSE_RANK() ranks employees based on the number of projects
โข The outer query returns all employees tied for the highest number of projects
This question tests your understanding of:
โ COUNT(DISTINCT)
โ GROUP BY
โ Window Functions DENSE_RANK
โ Ranking Aggregated Results
๐ฏ Expected Output Example
Employee ID | Total Projects
101 | 12
205 | 12
Both employees have worked on the highest number of distinct projects.
๐ Alternative Without Window Functions
SELECT
employee_id,
COUNT(DISTINCT project_id) AS total_projects
FROM employee_projects
GROUP BY employee_id
HAVING COUNT(DISTINCT project_id) = (
SELECT MAX(project_count)
FROM (
SELECT
COUNT(DISTINCT project_id) AS project_count
FROM employee_projects
GROUP BY employee_id
) t
);
This solution uses nested subqueries and MAX() instead of window functions.
๐ Tip for SQL Job Seekers:
Many interview questions involve ranking aggregated results, such as:
Highest number of projects, Most orders, Maximum sales, Highest attendance, Most logins
Practice combining GROUP BY with window functions like DENSE_RANK() to solve these efficiently.
โค๏ธ React with โค๏ธ for more interview challenges!
โค12๐2
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๐ Power BI Interview Challenge #1 ๐ฅ
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this Power BI problem.
You have a Sales table with the following columns:
Order Date
Sales
Create a DAX measure to calculate Year-to-Date (YTD) Sales.
๐ ๐ฒ: Challenge accepted! ๐ช
YTD Sales =
TOTALYTD(
SUM(Sales[Sales]),
Sales[Order Date]
)
๐ก Explanation:
TOTALYTD() calculates the cumulative sales from the beginning of the year up to the current date.
โข SUM(Sales) returns the total sales amount
โข Sales[Order Date] is the date column used for the YTD calculation
โข The measure automatically resets at the start of each new year[Sales]
๐ฏ Expected Output Example
Month | Sales | YTD Sales
--- | --- | ---
Jan | 10,000 | 10,000
Feb | 15,000 | 25,000
Mar | 12,000 | 37,000
Apr | 18,000 | 55,000
๐ Bonus (Using a Calendar Table)
YTD Sales =
TOTALYTD(
[Total Sales],
'Calendar'[Date]
)
Using a dedicated Calendar/Date table is considered a Power BI best practice and is recommended for all time intelligence calculations.
๐ Tip for Power BI Job Seekers:
Time Intelligence is one of the most frequently tested topics in Power BI interviews. Make sure you can confidently write measures for:
โข YTD (Year-to-Date)
โข MTD (Month-to-Date)
โข QTD (Quarter-to-Date)
โข Previous Year Sales
โข YoY Growth %
โข Rolling 12 Months
These are commonly used in business dashboards and technical interviews.
Power BI Resources: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c
โค๏ธ React with โค๏ธ for more Power BI interview challenges!
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this Power BI problem.
You have a Sales table with the following columns:
Order Date
Sales
Create a DAX measure to calculate Year-to-Date (YTD) Sales.
๐ ๐ฒ: Challenge accepted! ๐ช
YTD Sales =
TOTALYTD(
SUM(Sales[Sales]),
Sales[Order Date]
)
๐ก Explanation:
TOTALYTD() calculates the cumulative sales from the beginning of the year up to the current date.
โข SUM(Sales) returns the total sales amount
โข Sales[Order Date] is the date column used for the YTD calculation
โข The measure automatically resets at the start of each new year[Sales]
๐ฏ Expected Output Example
Month | Sales | YTD Sales
--- | --- | ---
Jan | 10,000 | 10,000
Feb | 15,000 | 25,000
Mar | 12,000 | 37,000
Apr | 18,000 | 55,000
๐ Bonus (Using a Calendar Table)
YTD Sales =
TOTALYTD(
[Total Sales],
'Calendar'[Date]
)
Using a dedicated Calendar/Date table is considered a Power BI best practice and is recommended for all time intelligence calculations.
๐ Tip for Power BI Job Seekers:
Time Intelligence is one of the most frequently tested topics in Power BI interviews. Make sure you can confidently write measures for:
โข YTD (Year-to-Date)
โข MTD (Month-to-Date)
โข QTD (Quarter-to-Date)
โข Previous Year Sales
โข YoY Growth %
โข Rolling 12 Months
These are commonly used in business dashboards and technical interviews.
Power BI Resources: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c
โค๏ธ React with โค๏ธ for more Power BI interview challenges!
โค14
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These FREE courses can help you learn Data Analytics, Power BI & Excel skills that companies actually hire for ๐
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โ Interactive Dashboards
โ Modern Analytics Skills
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โค2
๐ Power BI Interview Challenge #2 ๐ฅ
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this Power BI problem.
You have a Sales table with the columns: Order Date & Sales
Create a DAX measure to calculate Month-to-Date (MTD) Sales.
๐ ๐ฒ: Challenge accepted! ๐ช
MTD Sales =
TOTALMTD(
SUM(Sales[Sales]),
Sales[Order Date]
)
๐ก Explanation:
โข TOTALMTD() calculates cumulative sales from the beginning of the current month up to the selected date.
โข SUM(Sales) returns the total sales amount.
โข Sales[Order Date] is the date column used for the MTD calculation.
โข The measure automatically resets at the beginning of each new month.
๐ฏ Expected Output Example
Date | Sales | MTD Sales
Jul 1 | 2,000 | 2,000
Jul 2 | 3,500 | 5,500
Jul 3 | 1,500 | 7,000
Jul 4 | 4,000 | 11,000
๐ Bonus (Using a Calendar Table)
MTD Sales =
TOTALMTD(
[Total Sales],
'Calendar'[Date]
)
Using a dedicated Calendar table improves model performance and ensures accurate time intelligence calculations.
๐ Tip for Power BI Job Seekers:
Always create a proper Date Table and mark it as a Date Table in Power BI before using Time Intelligence functions. Many interview questions are designed to test this best practice.
Power BI Resources: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c
โค๏ธ React with โค๏ธ for more Power BI interview challenges!
๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐ฒ๐ฟ:
You have 2 minutes to solve this Power BI problem.
You have a Sales table with the columns: Order Date & Sales
Create a DAX measure to calculate Month-to-Date (MTD) Sales.
๐ ๐ฒ: Challenge accepted! ๐ช
MTD Sales =
TOTALMTD(
SUM(Sales[Sales]),
Sales[Order Date]
)
๐ก Explanation:
โข TOTALMTD() calculates cumulative sales from the beginning of the current month up to the selected date.
โข SUM(Sales) returns the total sales amount.
โข Sales[Order Date] is the date column used for the MTD calculation.
โข The measure automatically resets at the beginning of each new month.
๐ฏ Expected Output Example
Date | Sales | MTD Sales
Jul 1 | 2,000 | 2,000
Jul 2 | 3,500 | 5,500
Jul 3 | 1,500 | 7,000
Jul 4 | 4,000 | 11,000
๐ Bonus (Using a Calendar Table)
MTD Sales =
TOTALMTD(
[Total Sales],
'Calendar'[Date]
)
Using a dedicated Calendar table improves model performance and ensures accurate time intelligence calculations.
๐ Tip for Power BI Job Seekers:
Always create a proper Date Table and mark it as a Date Table in Power BI before using Time Intelligence functions. Many interview questions are designed to test this best practice.
Power BI Resources: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c
โค๏ธ React with โค๏ธ for more Power BI interview challenges!
โค8