SQL Interview Questions with Answers
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Most Asked SQL Interview Questions at MAANG Companiesπ₯π₯
Preparing for an SQL Interview at MAANG Companies? Here are some crucial SQL Questions you should be ready to tackle:
1. How do you retrieve all columns from a table?
SELECT * FROM table_name;
2. What SQL statement is used to filter records?
SELECT * FROM table_name
WHERE condition;
The WHERE clause is used to filter records based on a specified condition.
3. How can you join multiple tables? Describe different types of JOINs.
SELECT columns
FROM table1
JOIN table2 ON table1.column = table2.column
JOIN table3 ON table2.column = table3.column;
Types of JOINs:
1. INNER JOIN: Returns records with matching values in both tables
SELECT * FROM table1
INNER JOIN table2 ON table1.column = table2.column;
2. LEFT JOIN: Returns all records from the left table & matched records from the right table. Unmatched records will have NULL values.
SELECT * FROM table1
LEFT JOIN table2 ON table1.column = table2.column;
3. RIGHT JOIN: Returns all records from the right table & matched records from the left table. Unmatched records will have NULL values.
SELECT * FROM table1
RIGHT JOIN table2 ON table1.column = table2.column;
4. FULL JOIN: Returns records when there is a match in either left or right table. Unmatched records will have NULL values.
SELECT * FROM table1
FULL JOIN table2 ON table1.column = table2.column;
4. What is the difference between WHERE & HAVING clauses?
WHERE: Filters records before any groupings are made.
SELECT * FROM table_name
WHERE condition;
HAVING: Filters records after groupings are made.
SELECT column, COUNT(*)
FROM table_name
GROUP BY column
HAVING COUNT(*) > value;
5. How do you calculate average, sum, minimum & maximum values in a column?
Average: SELECT AVG(column_name) FROM table_name;
Sum: SELECT SUM(column_name) FROM table_name;
Minimum: SELECT MIN(column_name) FROM table_name;
Maximum: SELECT MAX(column_name) FROM table_name;
Here you can find essential SQL Interview Resourcesπ
https://t.iss.one/mysqldata
Like this post if you need more πβ€οΈ
Hope it helps :)
Preparing for an SQL Interview at MAANG Companies? Here are some crucial SQL Questions you should be ready to tackle:
1. How do you retrieve all columns from a table?
SELECT * FROM table_name;
2. What SQL statement is used to filter records?
SELECT * FROM table_name
WHERE condition;
The WHERE clause is used to filter records based on a specified condition.
3. How can you join multiple tables? Describe different types of JOINs.
SELECT columns
FROM table1
JOIN table2 ON table1.column = table2.column
JOIN table3 ON table2.column = table3.column;
Types of JOINs:
1. INNER JOIN: Returns records with matching values in both tables
SELECT * FROM table1
INNER JOIN table2 ON table1.column = table2.column;
2. LEFT JOIN: Returns all records from the left table & matched records from the right table. Unmatched records will have NULL values.
SELECT * FROM table1
LEFT JOIN table2 ON table1.column = table2.column;
3. RIGHT JOIN: Returns all records from the right table & matched records from the left table. Unmatched records will have NULL values.
SELECT * FROM table1
RIGHT JOIN table2 ON table1.column = table2.column;
4. FULL JOIN: Returns records when there is a match in either left or right table. Unmatched records will have NULL values.
SELECT * FROM table1
FULL JOIN table2 ON table1.column = table2.column;
4. What is the difference between WHERE & HAVING clauses?
WHERE: Filters records before any groupings are made.
SELECT * FROM table_name
WHERE condition;
HAVING: Filters records after groupings are made.
SELECT column, COUNT(*)
FROM table_name
GROUP BY column
HAVING COUNT(*) > value;
5. How do you calculate average, sum, minimum & maximum values in a column?
Average: SELECT AVG(column_name) FROM table_name;
Sum: SELECT SUM(column_name) FROM table_name;
Minimum: SELECT MIN(column_name) FROM table_name;
Maximum: SELECT MAX(column_name) FROM table_name;
Here you can find essential SQL Interview Resourcesπ
https://t.iss.one/mysqldata
Like this post if you need more πβ€οΈ
Hope it helps :)
β€4
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Iβm launching a Python Projects Series β designed for beginners to those preparing for technical interviews or building real-world projects.
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πΉ Week 1: Python Mini Projects (Daily Practice)
β¦ Calculator
β¦ To-Do List (CLI)
β¦ Number Guessing Game
β¦ Unit Converter
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β¦ Read/Write CSV & Excel files
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β¦ Currency Converter using Real-time API
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β¦ File Organizer Script
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β¦ Load & Clean CSV
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β¦ Predict House Prices
β¦ Email Spam Classifier
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Weβve officially hit 2.5 Million followers β and itβs time to level up together! β€οΈ
Iβm launching a Python Projects Series β designed for beginners to those preparing for technical interviews or building real-world projects.
This will be a step-by-step, hands-on journey β where youβll build useful Python projects with clear code, explanations, and mini-quizzes!
Hereβs what weβll cover:
πΉ Week 1: Python Mini Projects (Daily Practice)
β¦ Calculator
β¦ To-Do List (CLI)
β¦ Number Guessing Game
β¦ Unit Converter
β¦ Digital Clock
πΉ Week 2: Data Handling & APIs
β¦ Read/Write CSV & Excel files
β¦ JSON parsing
β¦ API Calls using Requests
β¦ Weather App using OpenWeather API
β¦ Currency Converter using Real-time API
πΉ Week 3: Automation with Python
β¦ File Organizer Script
β¦ Email Sender
β¦ WhatsApp Automation
β¦ PDF Merger
β¦ Excel Report Generator
πΉ Week 4: Data Analysis with Pandas & Matplotlib
β¦ Load & Clean CSV
β¦ Data Aggregation
β¦ Data Visualization
β¦ Trend Analysis
β¦ Dashboard Basics
πΉ Week 5: AI & ML Projects (Beginner Friendly)
β¦ Predict House Prices
β¦ Email Spam Classifier
β¦ Sentiment Analysis
β¦ Image Classification (Intro)
β¦ Basic Chatbot
π Each project includes:
β Problem Statement
β Code with explanation
β Sample input/output
β Learning outcome
β Mini quiz
π¬ React β€οΈ if you're ready to build some projects together!
You can access it for free here
ππ
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
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β€5
Questions & Answers for Data Analyst Interview
Question 1: Describe a time when you used data analysis to solve a business problem.
Ideal answer: This is your opportunity to showcase your data analysis skills in a real-world context. Be specific and provide examples of your work. For example, you could talk about a time when you used data analysis to identify customer churn, improve marketing campaigns, or optimize product development.
Question 2: What are some of the challenges you have faced in previous data analysis projects, and how did you overcome them?
Ideal answer: This question is designed to assess your problem-solving skills and your ability to learn from your experiences. Be honest and upfront about the challenges you have faced, but also focus on how you overcame them. For example, you could talk about a time when you had to deal with a large and messy dataset, or a time when you had to work with a tight deadline.
Question 3: How do you handle missing values in a dataset?
Ideal answer: Missing values are a common problem in data analysis, so it is important to know how to handle them properly. There are a variety of different methods that you can use, depending on the specific situation. For example, you could delete the rows with missing values, impute the missing values using a statistical method, or assign a default value to the missing values.
Question 4: How do you identify and remove outliers?
Ideal answer: Outliers are data points that are significantly different from the rest of the data. They can be caused by data errors or by natural variation in the data. It is important to identify and remove outliers before performing data analysis, as they can skew the results. There are a variety of different methods that you can use to identify outliers, such as the interquartile range (IQR) method or the standard deviation method.
Question 5: How do you interpret and communicate the results of your data analysis to non-technical audiences?
Ideal answer: It is important to be able to communicate your data analysis findings to both technical and non-technical audiences. When communicating to non-technical audiences, it is important to avoid using jargon and to focus on the key takeaways from your analysis. You can use data visualization tools to help you communicate your findings in a clear and concise way.
In addition to providing specific examples and answers to the questions, it is also important to be enthusiastic and demonstrate your passion for data analysis. Show the interviewer that you are excited about the opportunity to use your skills to solve real-world problems.
Question 1: Describe a time when you used data analysis to solve a business problem.
Ideal answer: This is your opportunity to showcase your data analysis skills in a real-world context. Be specific and provide examples of your work. For example, you could talk about a time when you used data analysis to identify customer churn, improve marketing campaigns, or optimize product development.
Question 2: What are some of the challenges you have faced in previous data analysis projects, and how did you overcome them?
Ideal answer: This question is designed to assess your problem-solving skills and your ability to learn from your experiences. Be honest and upfront about the challenges you have faced, but also focus on how you overcame them. For example, you could talk about a time when you had to deal with a large and messy dataset, or a time when you had to work with a tight deadline.
Question 3: How do you handle missing values in a dataset?
Ideal answer: Missing values are a common problem in data analysis, so it is important to know how to handle them properly. There are a variety of different methods that you can use, depending on the specific situation. For example, you could delete the rows with missing values, impute the missing values using a statistical method, or assign a default value to the missing values.
Question 4: How do you identify and remove outliers?
Ideal answer: Outliers are data points that are significantly different from the rest of the data. They can be caused by data errors or by natural variation in the data. It is important to identify and remove outliers before performing data analysis, as they can skew the results. There are a variety of different methods that you can use to identify outliers, such as the interquartile range (IQR) method or the standard deviation method.
Question 5: How do you interpret and communicate the results of your data analysis to non-technical audiences?
Ideal answer: It is important to be able to communicate your data analysis findings to both technical and non-technical audiences. When communicating to non-technical audiences, it is important to avoid using jargon and to focus on the key takeaways from your analysis. You can use data visualization tools to help you communicate your findings in a clear and concise way.
In addition to providing specific examples and answers to the questions, it is also important to be enthusiastic and demonstrate your passion for data analysis. Show the interviewer that you are excited about the opportunity to use your skills to solve real-world problems.
β€1
Top Libraries & Frameworks by Language ππ»
β― Python
ββ’ Pandas β Data Analysis
ββ’ NumPy β Math & Arrays
ββ’ Scikit-learn β Machine Learning
ββ’ TensorFlow / PyTorch β Deep Learning
ββ’ Flask / Django β Web Development
ββ’ OpenCV β Image Processing
β― JavaScript / TypeScript
ββ’ React β UI Development
ββ’ Vue β Lightweight SPAs
ββ’ Angular β Enterprise Apps
ββ’ Next.js β Full-Stack Web
ββ’ Express β Backend APIs
ββ’ Three.js β 3D Web Graphics
β― Java
ββ’ Spring Boot β Microservices
ββ’ Hibernate β ORM
ββ’ Apache Maven β Build Automation
ββ’ Apache Kafka β Real-Time Data
β― C++
ββ’ Boost β Utility Libraries
ββ’ Qt β GUI Applications
ββ’ Unreal Engine β Game Development
β― C#
ββ’ .NET / ASP.NET β Web Apps
ββ’ Unity β Game Development
ββ’ Entity Framework β ORM
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ββ’ ggplot2 β Data Visualization
ββ’ dplyr β Data Manipulation
ββ’ caret β Machine Learning
ββ’ Shiny β Interactive Dashboards
β― PHP
ββ’ Laravel β Full-Stack Web
ββ’ Symfony β Web Framework
ββ’ PHPUnit β Testing
β― Go (Golang)
ββ’ Gin β Web Framework
ββ’ Gorilla β Web Toolkit
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ββ’ Actix β Web Framework
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ββ’ Tokio β Async Runtime
Coding Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
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β― Python
ββ’ Pandas β Data Analysis
ββ’ NumPy β Math & Arrays
ββ’ Scikit-learn β Machine Learning
ββ’ TensorFlow / PyTorch β Deep Learning
ββ’ Flask / Django β Web Development
ββ’ OpenCV β Image Processing
β― JavaScript / TypeScript
ββ’ React β UI Development
ββ’ Vue β Lightweight SPAs
ββ’ Angular β Enterprise Apps
ββ’ Next.js β Full-Stack Web
ββ’ Express β Backend APIs
ββ’ Three.js β 3D Web Graphics
β― Java
ββ’ Spring Boot β Microservices
ββ’ Hibernate β ORM
ββ’ Apache Maven β Build Automation
ββ’ Apache Kafka β Real-Time Data
β― C++
ββ’ Boost β Utility Libraries
ββ’ Qt β GUI Applications
ββ’ Unreal Engine β Game Development
β― C#
ββ’ .NET / ASP.NET β Web Apps
ββ’ Unity β Game Development
ββ’ Entity Framework β ORM
β― R
ββ’ ggplot2 β Data Visualization
ββ’ dplyr β Data Manipulation
ββ’ caret β Machine Learning
ββ’ Shiny β Interactive Dashboards
β― PHP
ββ’ Laravel β Full-Stack Web
ββ’ Symfony β Web Framework
ββ’ PHPUnit β Testing
β― Go (Golang)
ββ’ Gin β Web Framework
ββ’ Gorilla β Web Toolkit
ββ’ GORM β ORM for Go
β― Rust
ββ’ Actix β Web Framework
ββ’ Rocket β Web Development
ββ’ Tokio β Async Runtime
Coding Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
React with β€οΈ for more useful content
β€5
Goldman Sachs senior data analyst interview asked questions
SQL
1 find avg of salaries department wise from table
2 Write a SQL query to see employee name and manager name using a self-join on 'employees' table with columns 'emp_id', 'name', and 'manager_id'.
3 newest joinee for every department (solved using lead lag)
POWER BI
1. What does Filter context in DAX mean?
2. Explain how to implement Row-Level Security (RLS) in Power BI.
3. Describe different types of filters in Power BI.
4. Explain the difference between 'ALL' and 'ALLSELECTED' in DAX.
5. How do you calculate the total sales for a specific product using DAX?
PYTHON
1. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys.
2. Find unique values in a list of assorted numbers and print the count of how many times each value is repeated.
3. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated.
I have curated best 80+ top-notch Data Analytics Resources ππ
https://t.iss.one/DataSimplifier
Hope this helps you π
SQL
1 find avg of salaries department wise from table
2 Write a SQL query to see employee name and manager name using a self-join on 'employees' table with columns 'emp_id', 'name', and 'manager_id'.
3 newest joinee for every department (solved using lead lag)
POWER BI
1. What does Filter context in DAX mean?
2. Explain how to implement Row-Level Security (RLS) in Power BI.
3. Describe different types of filters in Power BI.
4. Explain the difference between 'ALL' and 'ALLSELECTED' in DAX.
5. How do you calculate the total sales for a specific product using DAX?
PYTHON
1. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys.
2. Find unique values in a list of assorted numbers and print the count of how many times each value is repeated.
3. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated.
I have curated best 80+ top-notch Data Analytics Resources ππ
https://t.iss.one/DataSimplifier
Hope this helps you π
β€5
Follow this to optimise your linkedin profile ππ
Step 1: Upload a professional (looking) photo as this is your first impression
Step 2: Add your Industry and Location. Location is one of the top 5 fields that LinkedIn prioritizes when doing a key-word search. The other 4 fields are: Name, Headline, Summary and Experience.
Step 3: Customize your LinkedIn URL. To do this click on βEdit your public profileβ
Step 4: Write a summary. This is a great opportunity to communicate your brand, as well as, use your key words. As a starting point you can use summary from your resume.
Step 5: Describe your experience with relevant keywords.
Step 6: Add 5 or more relevant skills.
Step 7: List your education with specialization.
Step 8: Connect with 500+ contacts in your industry to expand your network.
Step 9: Turn ON βLet recruiters know youβre openβ
Step 1: Upload a professional (looking) photo as this is your first impression
Step 2: Add your Industry and Location. Location is one of the top 5 fields that LinkedIn prioritizes when doing a key-word search. The other 4 fields are: Name, Headline, Summary and Experience.
Step 3: Customize your LinkedIn URL. To do this click on βEdit your public profileβ
Step 4: Write a summary. This is a great opportunity to communicate your brand, as well as, use your key words. As a starting point you can use summary from your resume.
Step 5: Describe your experience with relevant keywords.
Step 6: Add 5 or more relevant skills.
Step 7: List your education with specialization.
Step 8: Connect with 500+ contacts in your industry to expand your network.
Step 9: Turn ON βLet recruiters know youβre openβ
β€2
π° DevOps Roadmap for Beginners 2025
βββ π§ What is DevOps? Principles & Culture
βββ π§ͺ Mini Task: Set up Local CI Pipeline with Shell Scripts
βββ βοΈ Linux Basics: Commands, Shell Scripting
βββ π Version Control: Git, GitHub, GitLab
βββ π§ͺ Mini Task: Automate Deployment via GitHub Actions
βββ π¦ Package Managers & Artifact Repositories (npm, pip, DockerHub)
βββ π³ Docker Essentials: Images, Containers, Volumes, Networks
βββ π§ͺ Mini Project: Dockerize a MERN App
βββ βοΈ CI/CD Concepts & Tools (Jenkins, GitHub Actions)
βββ π§ͺ Mini Project: CI/CD Pipeline for React App
βββ π§© Infrastructure as Code: Terraform / Ansible Basics
βββ π Monitoring & Logging: Prometheus, Grafana, ELK Stack
βββ π Secrets Management & Security Basics (Vault, .env)
βββ π Web Servers: Nginx, Apache (Reverse Proxy, Load Balancer)
βββ βοΈ Cloud Providers: AWS (EC2, S3, IAM), GCP, Azure Overview
React with β₯οΈ if you want me to explain each topic in detail
#devops
βββ π§ What is DevOps? Principles & Culture
βββ π§ͺ Mini Task: Set up Local CI Pipeline with Shell Scripts
βββ βοΈ Linux Basics: Commands, Shell Scripting
βββ π Version Control: Git, GitHub, GitLab
βββ π§ͺ Mini Task: Automate Deployment via GitHub Actions
βββ π¦ Package Managers & Artifact Repositories (npm, pip, DockerHub)
βββ π³ Docker Essentials: Images, Containers, Volumes, Networks
βββ π§ͺ Mini Project: Dockerize a MERN App
βββ βοΈ CI/CD Concepts & Tools (Jenkins, GitHub Actions)
βββ π§ͺ Mini Project: CI/CD Pipeline for React App
βββ π§© Infrastructure as Code: Terraform / Ansible Basics
βββ π Monitoring & Logging: Prometheus, Grafana, ELK Stack
βββ π Secrets Management & Security Basics (Vault, .env)
βββ π Web Servers: Nginx, Apache (Reverse Proxy, Load Balancer)
βββ βοΈ Cloud Providers: AWS (EC2, S3, IAM), GCP, Azure Overview
React with β₯οΈ if you want me to explain each topic in detail
#devops
β€7