🧠 How much SQL is enough to crack a Data Analyst Interview? 💼💻

📌 Basic Queries
⦁ SELECT, FROM, WHERE
⦁ DISTINCT, IN, BETWEEN, LIKE
⦁ ORDER BY, LIMIT

🔗 Joins and Relations
⦁ INNER JOIN, LEFT/RIGHT/FULL JOIN
⦁ Joining 2–3 tables in real life
⦁ Handling NULLs & duplicates

📊 Aggregate Functions
⦁ COUNT, SUM, AVG, MIN, MAX
⦁ GROUP BY multiple columns
⦁ HAVING vs WHERE filters

🧩 Subqueries & CTEs
⦁ Subqueries in SELECT, WHERE, FROM
⦁ WITH clause for clarity
⦁ Use in data cleaning & filtering

🔍 Window Functions
⦁ ROW_NUMBER, RANK, DENSE_RANK
⦁ LAG, LEAD for time analysis
⦁ PARTITION BY with OVER()

🛠️ Data Manipulation
⦁ CASE WHEN, COALESCE, NULLIF
⦁ Date funcs: DATE_TRUNC, DATEDIFF, NOW()
⦁ String funcs: SUBSTRING, CONCAT, UPPER

📊 Analytics-Focused Practice
⦁ KPI calc: revenue, conversions
⦁ Funnel, retention, user activity
⦁ Ad-hoc queries for business questions

📚 Common Interview Scenarios
⦁ Compare monthly metrics
⦁ Find top N customers/products
⦁ Detect duplicates or anomalies
⦁ Trend analysis with dates

✅ Must-Have Strengths
⦁ Clean, efficient queries
⦁ Clear logic explanation
⦁ Translating business asks to SQL
⦁ Spotting data patterns

💬 Tap ❤️ for more

🗄️ SQL Developer Roadmap

📂 SQL Basics (SELECT, WHERE, ORDER BY)
∟📂 Joins (INNER, LEFT, RIGHT, FULL)
∟📂 Aggregate Functions (COUNT, SUM, AVG)
∟📂 Grouping Data (GROUP BY, HAVING)
∟📂 Subqueries & Nested Queries
∟📂 Data Modification (INSERT, UPDATE, DELETE)
∟📂 Database Design (Normalization, Keys)
∟📂 Indexing & Query Optimization
∟📂 Stored Procedures & Functions
∟📂 Transactions & Locks
∟📂 Views & Triggers
∟📂 Backup & Restore
∟📂 Working with NoSQL basics (optional)
∟📂 Real Projects & Practice
∟✅ Apply for SQL Dev Roles

❤️ React for More!

🚀 SQL Command Essentials: DDL, DML, DCL, TCL 🚀

● DDL (Data Definition Language)
– CREATE: Make new tables/databases
– ALTER: Change table structure
– DROP: Delete tables/databases
– TRUNCATE: Remove all data, keep structure

● DML (Data Manipulation Language)
– SELECT: Retrieve data
– INSERT: Add data
– UPDATE: Change data
– DELETE: Remove data

● DCL (Data Control Language)
– GRANT: Give access rights
– REVOKE: Remove access rights

● TCL (Transaction Control Language)
– COMMIT: Save changes
– ROLLBACK: Undo changes
– SAVEPOINT: Set a point to rollback to
– BEGIN/END TRANSACTION: Mark begin/end of a transaction

React ❤️ if you found this helpful! 😊

✅ SQL Constraints! 🛡️

SQL constraints are rules applied to table columns to maintain accurate and reliable data.

🔹 PRIMARY KEY
– Uniquely identifies each row
– No NULLs allowed

🔹 FOREIGN KEY
– Links to a primary key in another table
– Maintains referential integrity

🔹 UNIQUE
– Ensures all values in a column are different

🔹 NOT NULL
– Column must have a value (can’t be empty)

🔹 CHECK
– Restricts the values in a column
👉 Example: CHECK (age >= 18)

🔹 DEFAULT
– Sets a default value if none is provided

Constraints prevent bad data from entering your database 💾

👍 Tap ❤️ if you found this helpful!

SQL Cheatsheet 📝

This SQL cheatsheet is designed to be your quick reference guide for SQL programming. Whether you’re a beginner learning how to query databases or an experienced developer looking for a handy resource, this cheatsheet covers essential SQL topics.

1. Database Basics
- CREATE DATABASE db_name;
- USE db_name;

2. Tables
- Create Table: CREATE TABLE table_name (col1 datatype, col2 datatype);
- Drop Table: DROP TABLE table_name;
- Alter Table: ALTER TABLE table_name ADD column_name datatype;

3. Insert Data
- INSERT INTO table_name (col1, col2) VALUES (val1, val2);

4. Select Queries
- Basic Select: SELECT * FROM table_name;
- Select Specific Columns: SELECT col1, col2 FROM table_name;
- Select with Condition: SELECT * FROM table_name WHERE condition;

5. Update Data
- UPDATE table_name SET col1 = value1 WHERE condition;

6. Delete Data
- DELETE FROM table_name WHERE condition;

7. Joins
- Inner Join: SELECT * FROM table1 INNER JOIN table2 ON table1.col = table2.col;
- Left Join: SELECT * FROM table1 LEFT JOIN table2 ON table1.col = table2.col;
- Right Join: SELECT * FROM table1 RIGHT JOIN table2 ON table1.col = table2.col;

8. Aggregations
- Count: SELECT COUNT(*) FROM table_name;
- Sum: SELECT SUM(col) FROM table_name;
- Group By: SELECT col, COUNT(*) FROM table_name GROUP BY col;

9. Sorting & Limiting
- Order By: SELECT * FROM table_name ORDER BY col ASC|DESC;
- Limit Results: SELECT * FROM table_name LIMIT n;

10. Indexes
- Create Index: CREATE INDEX idx_name ON table_name (col);
- Drop Index: DROP INDEX idx_name;

11. Subqueries
- SELECT * FROM table_name WHERE col IN (SELECT col FROM other_table);

12. Views
- Create View: CREATE VIEW view_name AS SELECT * FROM table_name;
- Drop View: DROP VIEW view_name;

✅ Top 7 Must-Prepare Topics for SQL Interviews (2025 Edition) 🗄️

✅ Basic SQL Queries – Master SELECT, FROM, WHERE, ORDER BY, LIMIT
✅ Joins – Understand INNER, LEFT, RIGHT, FULL OUTER JOIN (and when to use them)
✅ Aggregate Functions – Practice COUNT, SUM, AVG, MIN, MAX, GROUP BY, HAVING
✅ Subqueries – Learn nested queries and correlated subqueries
✅ Indexes – Know how to create and use indexes for performance optimization
✅ Window Functions – Understand RANK, ROW_NUMBER, LAG, LEAD (and their use cases)
✅ Data Modification – Practice INSERT, UPDATE, DELETE statements

These are the essentials to ace SQL interviews for data analyst, data engineer, or backend developer roles.

React with ❤️ for detailed explanation on each topic!

Data Analyst INTERVIEW QUESTIONS AND ANSWERS
👇👇

1.Can you name the wildcards in Excel?

Ans: There are 3 wildcards in Excel that can ve used in formulas.

Asterisk (*) – 0 or more characters. For example, Ex* could mean Excel, Extra, Expertise, etc.

Question mark (?) – Represents any 1 character. For example, R?ain may mean Rain or Ruin.

Tilde (~) – Used to identify a wildcard character (~, *, ?). For example, If you need to find the exact phrase India* in a list. If you use India* as the search string, you may get any word with India at the beginning followed by different characters (such as Indian, Indiana). If you have to look for India” exclusively, use ~.

Hence, the search string will be india~*. ~ is used to ensure that the spreadsheet reads the following character as is, and not as a wildcard.


2.What is cascading filter in tableau?

Ans: Cascading filters can also be understood as giving preference to a particular filter and then applying other filters on previously filtered data source. Right-click on the filter you want to use as a main filter and make sure it is set as all values in dashboard then select the subsequent filter and select only relevant values to cascade the filters. This will improve the performance of the dashboard as you have decreased the time wasted in running all the filters over complete data source.


3.What is the difference between .twb and .twbx extension?

Ans:
A .twb file contains information on all the sheets, dashboards and stories, but it won’t contain any information regarding data source. Whereas .twbx file contains all the sheets, dashboards, stories and also compressed data sources. For saving a .twbx extract needs to be performed on the data source. If we forward .twb file to someone else than they will be able to see the worksheets and dashboards but won’t be able to look into the dataset.


4.What are the various Power BI versions?

Power BI Premium capacity-based license, for example, allows users with a free license to act on content in workspaces with Premium capacity. A user with a free license can only use the Power BI service to connect to data and produce reports and dashboards in My Workspace outside of Premium capacity. They are unable to exchange material or publish it in other workspaces. To process material, a Power BI license with a free or Pro per-user license only uses a shared and restricted capacity. Users with a Power BI Pro license can only work with other Power BI Pro users if the material is stored in that shared capacity. They may consume user-generated information, post material to app workspaces, share dashboards, and subscribe to dashboards and reports. Pro users can share material with users who don’t have a Power BI Pro subnoscription while workspaces are at Premium capacity.

ENJOY LEARNING 👍👍

SQL Interview Questions

1. How would you find duplicate records in SQL?
2.What are various types of SQL joins?
3.What is a trigger in SQL?
4.What are different DDL,DML commands in SQL?
5.What is difference between Delete, Drop and Truncate?
6.What is difference between Union and Union all?
7.Which command give Unique values?
8. What is the difference between Where and Having Clause?
9.Give the execution of keywords in SQL?
10. What is difference between IN and BETWEEN Operator?
11. What is primary and Foreign key?
12. What is an aggregate Functions?
13. What is the difference between Rank and Dense Rank?
14. List the ACID Properties and explain what they are?
15. What is the difference between % and _ in like operator?
16. What does CTE stands for?
17. What is database?what is DBMS?What is RDMS?
18.What is Alias in SQL?
19. What is Normalisation?Describe various form?
20. How do you sort the results of a query?
21. Explain the types of Window functions?
22. What is limit and offset?
23. What is candidate key?
24. Describe various types of Alter command?
25. What is Cartesian product?

Like this post if you need more content like this ❤️

SQL can be simple—if you learn it the smart way..



If you’re aiming to become a data analyst, mastering SQL is non-negotiable.
Here’s a smart roadmap to ace it:

1. Basics First: Understand data types, simple queries (SELECT, FROM, WHERE). Master basic filtering.

2. Joins & Relationships: Dive into INNER, LEFT, RIGHT joins. Practice combining tables to extract meaningful insights.

3. Aggregations & Functions: Get comfortable with COUNT, SUM, AVG, MAX, GROUP BY, and HAVING clauses. These are essential for summarizing data.

4. Subqueries & Nested Queries: Learn how to query within queries. This is powerful for handling complex datasets.

5. Window Functions: Explore ranking, cumulative sums, and sliding windows to work with running totals and moving averages.

6. Optimization: Study indexing and query optimization for faster, more efficient queries.

7. Real-World Scenarios: Apply your SQL knowledge to solve real-world business problems.

The journey may seem tough, but each step sharpens your skills and brings you closer to data analysis excellence. Stay consistent, practice regularly, and let SQL become your superpower! 💪

Here you can find essential SQL Interview Resources👇
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

Like this post if you need more 👍❤️

Hope it helps :)

✔️📚A beginner's roadmap for learning SQL:

🔺Understand Basics:
Learn what SQL is and its purpose in managing relational databases.
Understand basic database concepts like tables, rows, columns, and relationships.

🔺Learn SQL Syntax:
Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE.
Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN.

🔺Setup a Database:
Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL.
Practice creating databases, tables, and inserting data.

🔺Retrieve Data (SELECT):
Learn to retrieve data from a database using SELECT statements.
Practice filtering data using WHERE clause and sorting using ORDER BY.

🔺Modify Data (INSERT, UPDATE, DELETE):
Understand how to insert new records, update existing ones, and delete data.
Be cautious with DELETE to avoid unintentional data loss.

🔺Working with Functions:
Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis.
Understand string functions, date functions, and mathematical functions.

🔺Data Filtering and Sorting:
Learn advanced filtering techniques using AND, OR, and IN operators.
Practice sorting data using multiple columns.

🔺Table Relationships (JOIN):
Understand the concept of joining tables to retrieve data from multiple tables.
Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

🔺Grouping and Aggregation:
Explore GROUP BY clause to group data based on specific columns.
Understand aggregate functions for summarizing data (SUM, AVG, COUNT).

🔺Subqueries:
Learn to use subqueries to perform complex queries.
Understand how to use subqueries in SELECT, WHERE, and FROM clauses.

🔺Indexes and Optimization:
Gain knowledge about indexes and their role in optimizing queries.
Understand how to optimize SQL queries for better performance.

🔺Transactions and ACID Properties:
Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability).
Understand how to use transactions to maintain data integrity.

🔺Normalization:
Understand the basics of database normalization to design efficient databases.
Learn about 1NF, 2NF, 3NF, and BCNF.

🔺Backup and Recovery:
Understand the importance of database backups.
Learn how to perform backups and recovery operations.

🔺Practice and Projects:
Apply your knowledge through hands-on projects.
Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects.

👀👍Remember to practice regularly and build real-world projects to reinforce your learning.

Happy Learning 🥳 📚

Here are some interview questions for both freshers and experienced applying for a data analyst #SQL

Analyst role:

#ForFreshers:
1. What is SQL, and why is it important in data analysis?
2. Explain the difference between a database and a table.
3. What are the basic SQL commands for data retrieval?
4. How do you retrieve all records from a table named "Employees"?
5. What is a primary key, and why is it important in a database?
6. What is a foreign key, and how is it used in SQL?
7. Describe the difference between SQL JOIN and SQL UNION.
8. How do you write a SQL query to find the second-highest salary in a table?
9. What is the purpose of the GROUP BY clause in SQL?
10. Can you explain the concept of normalization in SQL databases?
11. What are the common aggregate functions in SQL, and how are they used?

ForExperiencedCandidates:

1. Describe a scenario where you had to optimize a slow-running SQL query. How did you approach it?
2. Explain the differences between SQL Server, MySQL, and Oracle databases.
3. Can you describe the process of creating an index in a SQL database and its impact on query performance?
4. How do you handle data quality issues when performing data analysis with SQL?
5. What is a subquery, and when would you use it in SQL? Give an example of a complex SQL query you've written to extract specific insights from a database.
6. How do you handle NULL values in SQL, and what are the challenges associated with them?
7. Explain the ACID properties of a database and their importance.
8. What are stored procedures and triggers in SQL, and when would you use them?
9. Describe your experience with ETL (Extract, Transform, Load) processes using SQL.
10. Can you explain the concept of query optimization in SQL, and what techniques have you used for optimization?

Enjoy Learning 👍👍

✅ Complete Roadmap to Mastering SQL 🚀 🗄️

📂 1. SQL Fundamentals
– What is a database & DBMS
– Basic Syntax: SELECT, FROM, WHERE
– Data Types: INT, VARCHAR, DATE, etc.
– Operators: =, >, <, LIKE, IN
– Aliases & Comments

📂 2. Filtering & Sorting
– WHERE Clause: Advanced conditions
– ORDER BY: Sorting results
– LIMIT: Restricting rows
– DISTINCT: Unique values

📂 3. Aggregate Functions
– COUNT(), SUM(), AVG(), MIN(), MAX()
– GROUP BY: Grouping data
– HAVING: Filtering grouped data

📂 4. Joins & Relationships
– INNER JOIN: Matching rows
– LEFT/RIGHT JOIN: All rows from one table
– FULL OUTER JOIN: All rows from both tables
– Self Join: Joining a table to itself
– Subqueries: Queries within queries

📂 5. Advanced Filtering
– IN, BETWEEN, LIKE operators
– NULL values: IS NULL, IS NOT NULL
– EXISTS operator

📂 6. Subqueries & CTEs
– Subqueries in SELECT, FROM, WHERE
– Common Table Expressions (CTEs): Reusable queries

📂 7. Window Functions
– RANK(), DENSE_RANK(), ROW_NUMBER()
– LAG(), LEAD()
– OVER() clause: Defining the window
– Partitioning: PARTITION BY

📂 8. Data Manipulation
– INSERT: Adding new data
– UPDATE: Modifying existing data
– DELETE: Removing data
– MERGE: Combining data (upsert)

📂 9. Database Design
– Normalization: Reducing redundancy
– Primary & Foreign Keys: Relationships
– Data types & Constraints
– Indexing: Improving query performance

📂 10. Advanced Topics
– Stored Procedures: Precompiled SQL
– Triggers: Automatic actions
– Views: Virtual tables
– Performance Tuning: Optimizing queries
– Security: User permissions

📂 11. Practice & Projects
– Solve coding challenges on platforms like *LeetCode, HackerRank*
– Work on real-world projects using datasets from *Kaggle, Data.gov*
– Build a portfolio to showcase your SQL skills

💬 Tap ❤️ if you found this helpful!

✅ 20 Medium-Level SQL Interview Questions (with Detailed Answers)

1. Write a SQL query to find the second-highest salary.

SELECT MAX(salary) AS SecondHighestSalary
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

2. How would you optimize a slow SQL query?

•  Use appropriate indexes.
•  Avoid SELECT * and fetch only needed columns.
•  Rewrite correlated subqueries as joins.
•  Use EXPLAIN to analyze query plan.
•  Break complex queries into CTEs.

3. What is the difference between INNER JOIN and OUTER JOIN?

•  INNER JOIN: Returns only matching rows between tables.
•  OUTER JOIN: Includes matching rows and non-matching rows with NULLs (LEFT, RIGHT, FULL).

4. Write a SQL query to find the top 3 departments with the highest average salary.

SELECT department_id, AVG(salary) AS avg_salary
FROM employees
GROUP BY department_id
ORDER BY avg_salary DESC
LIMIT 3;

5. How do you handle duplicate rows in a SQL query?

Use DISTINCT, or use ROW_NUMBER() in a CTE and filter rows:

WITH cte AS (
  SELECT *, ROW_NUMBER() OVER (PARTITION BY name, department_id ORDER BY id) AS rn
  FROM employees
)
DELETE FROM cte WHERE rn > 1;

6. Write a SQL query to find the employees who have the same name and work in the same department.

SELECT name, department_id
FROM employees
GROUP BY name, department_id
HAVING COUNT(*) > 1;

7. What is the difference between UNION and UNION ALL?

•  UNION: Removes duplicates.
•  UNION ALL: Keeps all records including duplicates.

8. Write a SQL query to find the departments with no employees.

SELECT d.department_id, d.department_name
FROM departments d
LEFT JOIN employees e ON d.department_id = e.department_id
WHERE e.employee_id IS NULL;

9. How do you use indexing to improve SQL query performance?

•  Indexes reduce the data scanned by filtering or joining.
•  Create indexes on frequently used WHERE, JOIN, and ORDER BY columns.

10. Write a SQL query to find the employees who have worked for more than 5 years.

SELECT *
FROM employees
WHERE DATEDIFF(CURDATE(), hire_date) > 5 * 365;

11. What is the difference between SUBQUERY and JOIN?

•  Subquery: Query inside another query, can be nested.
•  Join: Combines rows from multiple tables based on related columns.

12. Write a SQL query to find the top 2 products with the highest sales.

SELECT product_id, SUM(sales) AS total_sales
FROM sales_table
GROUP BY product_id
ORDER BY total_sales DESC
LIMIT 2;

13. How do you use stored procedures to improve SQL query performance?

•  Pre-compiled and cached.
•  Reduces network traffic with multiple operations in one call.
•  Enhances modularity and reusability.

14. Write a SQL query to find the customers who have placed an order but have not made a payment.

SELECT o.customer_id
FROM orders o
LEFT JOIN payments p ON o.order_id = p.order_id
WHERE p.payment_id IS NULL;

15. What is the difference between GROUP BY and HAVING?

•  GROUP BY: Groups rows based on one or more columns.
•  HAVING: Filters groups, like WHERE but for aggregated data.

16. Write a SQL query to find the employees who work in the same department as their manager.

SELECT e.employee_id, e.name
FROM employees e
JOIN employees m ON e.department_id = m.department_id AND e.manager_id = m.employee_id;

17. How do you use window functions to solve complex queries?

•  Use ROW_NUMBER(), RANK(), SUM() OVER(), LAG() etc.
•  They perform calculations across rows without collapsing them.

18. Write a SQL query to find the top 3 products with the highest average price.

SELECT product_id, AVG(price) AS avg_price
FROM products
GROUP BY product_id
ORDER BY avg_price DESC
LIMIT 3;

19. What is the difference between TRUNCATE and DELETE?

•  TRUNCATE: Removes all rows, faster, can’t rollback in most DBs.
•  DELETE: Removes selected rows, supports WHERE, and rollback.

20. Write a SQL query to find the employees who have not taken any leave in the last 6 months.

SELECT e.*
FROM employees e
LEFT JOIN leaves l ON e.employee_id = l.employee_id AND l.leave_date >= DATE_SUB(CURDATE(), INTERVAL 6 MONTH)
WHERE l.leave_id IS NULL;