Data Analyst Interview Questions & Preparation Tips
Be prepared with a mix of technical, analytical, and business-oriented interview questions.
1. Technical Questions (Data Analysis & Reporting)
SQL Questions:
How do you write a query to fetch the top 5 highest revenue-generating customers?
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN.
How would you optimize a slow-running query?
What are CTEs and when would you use them?
Data Visualization (Power BI / Tableau / Excel)
How would you create a dashboard to track key performance metrics?
Explain the difference between measures and calculated columns in Power BI.
How do you handle missing data in Tableau?
What are DAX functions, and can you give an example?
ETL & Data Processing (Alteryx, Power BI, Excel)
What is ETL, and how does it relate to BI?
Have you used Alteryx for data transformation? Explain a complex workflow you built.
How do you automate reporting using Power Query in Excel?
2. Business and Analytical Questions
How do you define KPIs for a business process?
Give an example of how you used data to drive a business decision.
How would you identify cost-saving opportunities in a reporting process?
Explain a time when your report uncovered a hidden business insight.
3. Scenario-Based & Behavioral Questions
Stakeholder Management:
How do you handle a situation where different business units have conflicting reporting requirements?
How do you explain complex data insights to non-technical stakeholders?
Problem-Solving & Debugging:
What would you do if your report is showing incorrect numbers?
How do you ensure the accuracy of a new KPI you introduced?
Project Management & Process Improvement:
Have you led a project to automate or improve a reporting process?
What steps do you take to ensure the timely delivery of reports?
4. Industry-Specific Questions (Credit Reporting & Financial Services)
What are some key credit risk metrics used in financial services?
How would you analyze trends in customer credit behavior?
How do you ensure compliance and data security in reporting?
5. General HR Questions
Why do you want to work at this company?
Tell me about a challenging project and how you handled it.
What are your strengths and weaknesses?
Where do you see yourself in five years?
How to Prepare?
Brush up on SQL, Power BI, and ETL tools (especially Alteryx).
Learn about key financial and credit reporting metrics.(varies company to company)
Practice explaining data-driven insights in a business-friendly manner.
Be ready to showcase problem-solving skills with real-world examples.
React with ❤️ if you want me to also post sample answer for the above questions
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
Be prepared with a mix of technical, analytical, and business-oriented interview questions.
1. Technical Questions (Data Analysis & Reporting)
SQL Questions:
How do you write a query to fetch the top 5 highest revenue-generating customers?
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN.
How would you optimize a slow-running query?
What are CTEs and when would you use them?
Data Visualization (Power BI / Tableau / Excel)
How would you create a dashboard to track key performance metrics?
Explain the difference between measures and calculated columns in Power BI.
How do you handle missing data in Tableau?
What are DAX functions, and can you give an example?
ETL & Data Processing (Alteryx, Power BI, Excel)
What is ETL, and how does it relate to BI?
Have you used Alteryx for data transformation? Explain a complex workflow you built.
How do you automate reporting using Power Query in Excel?
2. Business and Analytical Questions
How do you define KPIs for a business process?
Give an example of how you used data to drive a business decision.
How would you identify cost-saving opportunities in a reporting process?
Explain a time when your report uncovered a hidden business insight.
3. Scenario-Based & Behavioral Questions
Stakeholder Management:
How do you handle a situation where different business units have conflicting reporting requirements?
How do you explain complex data insights to non-technical stakeholders?
Problem-Solving & Debugging:
What would you do if your report is showing incorrect numbers?
How do you ensure the accuracy of a new KPI you introduced?
Project Management & Process Improvement:
Have you led a project to automate or improve a reporting process?
What steps do you take to ensure the timely delivery of reports?
4. Industry-Specific Questions (Credit Reporting & Financial Services)
What are some key credit risk metrics used in financial services?
How would you analyze trends in customer credit behavior?
How do you ensure compliance and data security in reporting?
5. General HR Questions
Why do you want to work at this company?
Tell me about a challenging project and how you handled it.
What are your strengths and weaknesses?
Where do you see yourself in five years?
How to Prepare?
Brush up on SQL, Power BI, and ETL tools (especially Alteryx).
Learn about key financial and credit reporting metrics.(varies company to company)
Practice explaining data-driven insights in a business-friendly manner.
Be ready to showcase problem-solving skills with real-world examples.
React with ❤️ if you want me to also post sample answer for the above questions
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
❤6
Best way to prepare for a SQL interviews 👇👇
1. Review Basic Concepts: Ensure you understand fundamental SQL concepts like SELECT statements, JOINs, GROUP BY, and WHERE clauses.
2. Practice SQL Queries: Work on writing and executing SQL queries. Practice retrieving, updating, and deleting data.
3. Understand Database Design: Learn about normalization, indexes, and relationships to comprehend how databases are structured.
4. Know Your Database: If possible, find out which database system the company uses (e.g., MySQL, PostgreSQL, SQL Server) and familiarize yourself with its specific syntax.
5. Data Types and Constraints: Understand various data types and constraints such as PRIMARY KEY, FOREIGN KEY, and UNIQUE constraints.
6. Stored Procedures and Functions: Learn about stored procedures and functions, as interviewers may inquire about these.
7. Data Manipulation Language (DML): Be familiar with INSERT, UPDATE, and DELETE statements.
8. Data Definition Language (DDL): Understand statements like CREATE, ALTER, and DROP for database and table management.
9. Normalization and Optimization: Brush up on database normalization and optimization techniques to demonstrate your understanding of efficient database design.
10. Troubleshooting Skills: Be prepared to troubleshoot queries, identify errors, and optimize poorly performing queries.
11. Scenario-Based Questions: Practice answering scenario-based questions. Understand how to approach problems and design solutions.
12. Latest Trends: Stay updated on the latest trends in database technologies and SQL best practices.
13. Review Resume Projects: If you have projects involving SQL on your resume, be ready to discuss them in detail.
14. Mock Interviews: Conduct mock interviews with a friend or use online platforms to simulate real interview scenarios.
15. Ask Questions: Prepare questions to ask the interviewer about the company's use of databases and SQL.
Best Resources to learn SQL 👇
SQL Topics for Data Analysts
Download SQL Cheatsheet
SQL Interview Questions
Learn & Practice SQL
Also try to apply what you learn through hands-on projects or challenges.
Please give us credits while sharing: -> https://news.1rj.ru/str/free4unow_backup
ENJOY LEARNING 👍👍
1. Review Basic Concepts: Ensure you understand fundamental SQL concepts like SELECT statements, JOINs, GROUP BY, and WHERE clauses.
2. Practice SQL Queries: Work on writing and executing SQL queries. Practice retrieving, updating, and deleting data.
3. Understand Database Design: Learn about normalization, indexes, and relationships to comprehend how databases are structured.
4. Know Your Database: If possible, find out which database system the company uses (e.g., MySQL, PostgreSQL, SQL Server) and familiarize yourself with its specific syntax.
5. Data Types and Constraints: Understand various data types and constraints such as PRIMARY KEY, FOREIGN KEY, and UNIQUE constraints.
6. Stored Procedures and Functions: Learn about stored procedures and functions, as interviewers may inquire about these.
7. Data Manipulation Language (DML): Be familiar with INSERT, UPDATE, and DELETE statements.
8. Data Definition Language (DDL): Understand statements like CREATE, ALTER, and DROP for database and table management.
9. Normalization and Optimization: Brush up on database normalization and optimization techniques to demonstrate your understanding of efficient database design.
10. Troubleshooting Skills: Be prepared to troubleshoot queries, identify errors, and optimize poorly performing queries.
11. Scenario-Based Questions: Practice answering scenario-based questions. Understand how to approach problems and design solutions.
12. Latest Trends: Stay updated on the latest trends in database technologies and SQL best practices.
13. Review Resume Projects: If you have projects involving SQL on your resume, be ready to discuss them in detail.
14. Mock Interviews: Conduct mock interviews with a friend or use online platforms to simulate real interview scenarios.
15. Ask Questions: Prepare questions to ask the interviewer about the company's use of databases and SQL.
Best Resources to learn SQL 👇
SQL Topics for Data Analysts
Download SQL Cheatsheet
SQL Interview Questions
Learn & Practice SQL
Also try to apply what you learn through hands-on projects or challenges.
Please give us credits while sharing: -> https://news.1rj.ru/str/free4unow_backup
ENJOY LEARNING 👍👍
❤4
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SQL Interview Questions for 0-1 year of Experience (Asked in Top Product-Based Companies).
Sharpen your SQL skills with these real interview questions!
Q1. Customer Purchase Patterns -
You have two tables, Customers and Purchases: CREATE TABLE Customers ( customer_id INT PRIMARY KEY, customer_name VARCHAR(255) ); CREATE TABLE Purchases ( purchase_id INT PRIMARY KEY, customer_id INT, product_id INT, purchase_date DATE );
Assume necessary INSERT statements are already executed.
Write an SQL query to find the names of customers who have purchased more than 5 different products within the last month. Order the result by customer_name.
Q2. Call Log Analysis -
Suppose you have a CallLogs table: CREATE TABLE CallLogs ( log_id INT PRIMARY KEY, caller_id INT, receiver_id INT, call_start_time TIMESTAMP, call_end_time TIMESTAMP );
Assume necessary INSERT statements are already executed.
Write a query to find the average call duration per user. Include only users who have made more than 10 calls in total. Order the result by average duration descending.
Q3. Employee Project Allocation - Consider two tables, Employees and Projects:
CREATE TABLE Employees ( employee_id INT PRIMARY KEY, employee_name VARCHAR(255), department VARCHAR(255) ); CREATE TABLE Projects ( project_id INT PRIMARY KEY, lead_employee_id INT, project_name VARCHAR(255), start_date DATE, end_date DATE );
Assume necessary INSERT statements are already executed.
The goal is to write an SQL query to find the names of employees who have led more than 3 projects in the last year. The result should be ordered by the number of projects led.
Sharpen your SQL skills with these real interview questions!
Q1. Customer Purchase Patterns -
You have two tables, Customers and Purchases: CREATE TABLE Customers ( customer_id INT PRIMARY KEY, customer_name VARCHAR(255) ); CREATE TABLE Purchases ( purchase_id INT PRIMARY KEY, customer_id INT, product_id INT, purchase_date DATE );
Assume necessary INSERT statements are already executed.
Write an SQL query to find the names of customers who have purchased more than 5 different products within the last month. Order the result by customer_name.
Q2. Call Log Analysis -
Suppose you have a CallLogs table: CREATE TABLE CallLogs ( log_id INT PRIMARY KEY, caller_id INT, receiver_id INT, call_start_time TIMESTAMP, call_end_time TIMESTAMP );
Assume necessary INSERT statements are already executed.
Write a query to find the average call duration per user. Include only users who have made more than 10 calls in total. Order the result by average duration descending.
Q3. Employee Project Allocation - Consider two tables, Employees and Projects:
CREATE TABLE Employees ( employee_id INT PRIMARY KEY, employee_name VARCHAR(255), department VARCHAR(255) ); CREATE TABLE Projects ( project_id INT PRIMARY KEY, lead_employee_id INT, project_name VARCHAR(255), start_date DATE, end_date DATE );
Assume necessary INSERT statements are already executed.
The goal is to write an SQL query to find the names of employees who have led more than 3 projects in the last year. The result should be ordered by the number of projects led.
❤5
Many people ask this common question “Can I get a job with just SQL and Excel?” or “Can I get a job with just Power BI and Python?”.
The answer to all of those questions is yes.
There are jobs that use only SQL, Tableau, Power BI, Excel, Python, or R or some combination of those.
However, the combination of tools you learn impacts the total number of jobs you are qualified for.
For example, let’s say with just SQL and Excel you are qualified for 10 jobs, but if you add Tableau to that, you are qualified for 50 jobs.
If you have a success rate of landing a job you’re qualified for of 4%, having 5 times as many jobs to go for greatly improves your odds of landing a job.
Does this mean you should go out there and learn every single skill any data analyst job requires?
NO!
It’s about finding the core tools that many jobs want.
And, in my opinion, those tools are SQL, Excel, and a visualization tool.
With these three tools, you are qualified for the majority of entry level data jobs and many higher level jobs.
So, you can land a job with whatever tools you’re comfortable with.
But if you have the three tools above in your toolbelt, you will have many more jobs to apply for and greatly improve your chances of snagging one.
The answer to all of those questions is yes.
There are jobs that use only SQL, Tableau, Power BI, Excel, Python, or R or some combination of those.
However, the combination of tools you learn impacts the total number of jobs you are qualified for.
For example, let’s say with just SQL and Excel you are qualified for 10 jobs, but if you add Tableau to that, you are qualified for 50 jobs.
If you have a success rate of landing a job you’re qualified for of 4%, having 5 times as many jobs to go for greatly improves your odds of landing a job.
Does this mean you should go out there and learn every single skill any data analyst job requires?
NO!
It’s about finding the core tools that many jobs want.
And, in my opinion, those tools are SQL, Excel, and a visualization tool.
With these three tools, you are qualified for the majority of entry level data jobs and many higher level jobs.
So, you can land a job with whatever tools you’re comfortable with.
But if you have the three tools above in your toolbelt, you will have many more jobs to apply for and greatly improve your chances of snagging one.
❤2
Quick SQL functions cheat sheet for beginners
Aggregate Functions
COUNT(*): Counts rows.
SUM(column): Total sum.
AVG(column): Average value.
MAX(column): Maximum value.
MIN(column): Minimum value.
String Functions
CONCAT(a, b, …): Concatenates strings.
SUBSTRING(s, start, length): Extracts part of a string.
UPPER(s) / LOWER(s): Converts string case.
TRIM(s): Removes leading/trailing spaces.
Date & Time Functions
CURRENT_DATE / CURRENT_TIME / CURRENT_TIMESTAMP: Current date/time.
EXTRACT(unit FROM date): Retrieves a date part (e.g., year, month).
DATE_ADD(date, INTERVAL n unit): Adds an interval to a date.
Numeric Functions
ROUND(num, decimals): Rounds to a specified decimal.
CEIL(num) / FLOOR(num): Rounds up/down.
ABS(num): Absolute value.
MOD(a, b): Returns the remainder.
Control Flow Functions
CASE: Conditional logic.
COALESCE(val1, val2, …): Returns the first non-null value.
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Hope it helps :)
#dataanalytics
Aggregate Functions
COUNT(*): Counts rows.
SUM(column): Total sum.
AVG(column): Average value.
MAX(column): Maximum value.
MIN(column): Minimum value.
String Functions
CONCAT(a, b, …): Concatenates strings.
SUBSTRING(s, start, length): Extracts part of a string.
UPPER(s) / LOWER(s): Converts string case.
TRIM(s): Removes leading/trailing spaces.
Date & Time Functions
CURRENT_DATE / CURRENT_TIME / CURRENT_TIMESTAMP: Current date/time.
EXTRACT(unit FROM date): Retrieves a date part (e.g., year, month).
DATE_ADD(date, INTERVAL n unit): Adds an interval to a date.
Numeric Functions
ROUND(num, decimals): Rounds to a specified decimal.
CEIL(num) / FLOOR(num): Rounds up/down.
ABS(num): Absolute value.
MOD(a, b): Returns the remainder.
Control Flow Functions
CASE: Conditional logic.
COALESCE(val1, val2, …): Returns the first non-null value.
Like for more free Cheatsheets ❤️
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
#dataanalytics
❤3
If you’re a Data Analyst, chances are you use 𝐒𝐐𝐋 every single day. And if you’re preparing for interviews, you’ve probably realized that it's not just about writing queries it's about writing smart, efficient, and scalable ones.
1. 𝐁𝐫𝐞𝐚𝐤 𝐈𝐭 𝐃𝐨𝐰𝐧 𝐰𝐢𝐭𝐡 𝐂𝐓𝐄𝐬 (𝐂𝐨𝐦𝐦𝐨𝐧 𝐓𝐚𝐛𝐥𝐞 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧𝐬)
Ever worked on a query that became an unreadable monster? CTEs let you break that down into logical steps. You can treat them like temporary views — great for simplifying logic and improving collaboration across your team.
2. 𝐔𝐬𝐞 𝐖𝐢𝐧𝐝𝐨𝐰 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬
Forget the mess of subqueries. With functions like ROW_NUMBER(), RANK(), LEAD() and LAG(), you can compare rows, rank items, or calculate running totals — all within the same query. Total
3. 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬 (𝐍𝐞𝐬𝐭𝐞𝐝 𝐐𝐮𝐞𝐫𝐢𝐞𝐬)
Yes, they're old school, but nested subqueries are still powerful. Use them when you want to filter based on results of another query or isolate logic step-by-step before joining with the big picture.
4. 𝐈𝐧𝐝𝐞𝐱𝐞𝐬 & 𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧
Query taking forever? Look at your indexes. Index the columns you use in JOINs, WHERE, and GROUP BY. Even basic knowledge of how the SQL engine reads data can take your skills up a notch.
5. 𝐉𝐨𝐢𝐧𝐬 𝐯𝐬. 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬
Joins are usually faster and better for combining large datasets. Subqueries, on the other hand, are cleaner when doing one-off filters or smaller operations. Choose wisely based on the context.
6. 𝐂𝐀𝐒𝐄 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭𝐬:
Want to categorize or bucket data without creating a separate table? Use CASE. It’s ideal for conditional logic, custom labels, and grouping in a single query.
7. 𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐆𝐑𝐎𝐔𝐏 𝐁𝐘
Most analytics questions start with "how many", "what’s the average", or "which is the highest?". SUM(), COUNT(), AVG(), etc., and pair them with GROUP BY to drive insights that matter.
8. 𝐃𝐚𝐭𝐞𝐬 𝐀𝐫𝐞 𝐀𝐥𝐰𝐚𝐲𝐬 𝐓𝐫𝐢𝐜𝐤𝐲
Time-based analysis is everywhere: trends, cohorts, seasonality, etc. Get familiar with functions like DATEADD, DATEDIFF, DATE_TRUNC, and DATEPART to work confidently with time series data.
9. 𝐒𝐞𝐥𝐟-𝐉𝐨𝐢𝐧𝐬 & 𝐑𝐞𝐜𝐮𝐫𝐬𝐢𝐯𝐞 𝐐𝐮𝐞𝐫𝐢𝐞𝐬 𝐟𝐨𝐫 𝐇𝐢𝐞𝐫𝐚𝐫𝐜𝐡𝐢𝐞𝐬
Whether it's org charts or product categories, not all data is flat. Learn how to join a table to itself or use recursive CTEs to navigate parent-child relationships effectively.
You don’t need to memorize 100 functions. You need to understand 10 really well and apply them smartly. These are the concepts I keep going back to not just in interviews, but in the real world where clarity, performance, and logic matter most.
1. 𝐁𝐫𝐞𝐚𝐤 𝐈𝐭 𝐃𝐨𝐰𝐧 𝐰𝐢𝐭𝐡 𝐂𝐓𝐄𝐬 (𝐂𝐨𝐦𝐦𝐨𝐧 𝐓𝐚𝐛𝐥𝐞 𝐄𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧𝐬)
Ever worked on a query that became an unreadable monster? CTEs let you break that down into logical steps. You can treat them like temporary views — great for simplifying logic and improving collaboration across your team.
2. 𝐔𝐬𝐞 𝐖𝐢𝐧𝐝𝐨𝐰 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬
Forget the mess of subqueries. With functions like ROW_NUMBER(), RANK(), LEAD() and LAG(), you can compare rows, rank items, or calculate running totals — all within the same query. Total
3. 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬 (𝐍𝐞𝐬𝐭𝐞𝐝 𝐐𝐮𝐞𝐫𝐢𝐞𝐬)
Yes, they're old school, but nested subqueries are still powerful. Use them when you want to filter based on results of another query or isolate logic step-by-step before joining with the big picture.
4. 𝐈𝐧𝐝𝐞𝐱𝐞𝐬 & 𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧
Query taking forever? Look at your indexes. Index the columns you use in JOINs, WHERE, and GROUP BY. Even basic knowledge of how the SQL engine reads data can take your skills up a notch.
5. 𝐉𝐨𝐢𝐧𝐬 𝐯𝐬. 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬
Joins are usually faster and better for combining large datasets. Subqueries, on the other hand, are cleaner when doing one-off filters or smaller operations. Choose wisely based on the context.
6. 𝐂𝐀𝐒𝐄 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭𝐬:
Want to categorize or bucket data without creating a separate table? Use CASE. It’s ideal for conditional logic, custom labels, and grouping in a single query.
7. 𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐆𝐑𝐎𝐔𝐏 𝐁𝐘
Most analytics questions start with "how many", "what’s the average", or "which is the highest?". SUM(), COUNT(), AVG(), etc., and pair them with GROUP BY to drive insights that matter.
8. 𝐃𝐚𝐭𝐞𝐬 𝐀𝐫𝐞 𝐀𝐥𝐰𝐚𝐲𝐬 𝐓𝐫𝐢𝐜𝐤𝐲
Time-based analysis is everywhere: trends, cohorts, seasonality, etc. Get familiar with functions like DATEADD, DATEDIFF, DATE_TRUNC, and DATEPART to work confidently with time series data.
9. 𝐒𝐞𝐥𝐟-𝐉𝐨𝐢𝐧𝐬 & 𝐑𝐞𝐜𝐮𝐫𝐬𝐢𝐯𝐞 𝐐𝐮𝐞𝐫𝐢𝐞𝐬 𝐟𝐨𝐫 𝐇𝐢𝐞𝐫𝐚𝐫𝐜𝐡𝐢𝐞𝐬
Whether it's org charts or product categories, not all data is flat. Learn how to join a table to itself or use recursive CTEs to navigate parent-child relationships effectively.
You don’t need to memorize 100 functions. You need to understand 10 really well and apply them smartly. These are the concepts I keep going back to not just in interviews, but in the real world where clarity, performance, and logic matter most.
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SQL From Basic to Advanced level
Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, <=, >=, <> etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.
Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.
Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all
- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -
Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.
This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.
Remember that practice is the key here. It will be more clear and perfect with the continous practice
Best telegram channel to learn SQL: https://news.1rj.ru/str/sqlanalyst
Data Analyst Jobs👇
https://news.1rj.ru/str/jobs_SQL
Join @free4unow_backup for more free resources.
Like this post if it helps 😄❤️
ENJOY LEARNING 👍👍
Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, <=, >=, <> etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.
Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.
Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all
- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -
Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.
This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.
Remember that practice is the key here. It will be more clear and perfect with the continous practice
Best telegram channel to learn SQL: https://news.1rj.ru/str/sqlanalyst
Data Analyst Jobs👇
https://news.1rj.ru/str/jobs_SQL
Join @free4unow_backup for more free resources.
Like this post if it helps 😄❤️
ENJOY LEARNING 👍👍
❤9
SQL interview questions with answers 😄👇
1. Question: What is SQL?
Answer: SQL (Structured Query Language) is a programming language designed for managing and manipulating relational databases. It is used to query, insert, update, and delete data in databases.
2. Question: Differentiate between SQL and MySQL.
Answer: SQL is a language for managing relational databases, while MySQL is an open-source relational database management system (RDBMS) that uses SQL as its language.
3. Question: Explain the difference between INNER JOIN and LEFT JOIN.
Answer: INNER JOIN returns rows when there is a match in both tables, while LEFT JOIN returns all rows from the left table and the matched rows from the right table, filling in with NULLs for non-matching rows.
4. Question: How do you remove duplicate records from a table?
Answer: Use the
5. Question: What is a subquery in SQL?
Answer: A subquery is a query nested inside another query. It can be used to retrieve data that will be used in the main query as a condition to further restrict the data to be retrieved.
6. Question: Explain the purpose of the GROUP BY clause.
Answer: The GROUP BY clause is used to group rows that have the same values in specified columns into summary rows, like when using aggregate functions such as COUNT, SUM, AVG, etc.
7. Question: How can you add a new record to a table?
Answer: Use the
8. Question: What is the purpose of the HAVING clause?
Answer: The HAVING clause is used in combination with the GROUP BY clause to filter the results of aggregate functions based on a specified condition.
9. Question: Explain the concept of normalization in databases.
Answer: Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves breaking down tables into smaller, related tables.
10. Question: How do you update data in a table in SQL?
Answer: Use the
Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
1. Question: What is SQL?
Answer: SQL (Structured Query Language) is a programming language designed for managing and manipulating relational databases. It is used to query, insert, update, and delete data in databases.
2. Question: Differentiate between SQL and MySQL.
Answer: SQL is a language for managing relational databases, while MySQL is an open-source relational database management system (RDBMS) that uses SQL as its language.
3. Question: Explain the difference between INNER JOIN and LEFT JOIN.
Answer: INNER JOIN returns rows when there is a match in both tables, while LEFT JOIN returns all rows from the left table and the matched rows from the right table, filling in with NULLs for non-matching rows.
4. Question: How do you remove duplicate records from a table?
Answer: Use the
DISTINCT keyword in a SELECT statement to retrieve unique records. For example: SELECT DISTINCT column1, column2 FROM table;5. Question: What is a subquery in SQL?
Answer: A subquery is a query nested inside another query. It can be used to retrieve data that will be used in the main query as a condition to further restrict the data to be retrieved.
6. Question: Explain the purpose of the GROUP BY clause.
Answer: The GROUP BY clause is used to group rows that have the same values in specified columns into summary rows, like when using aggregate functions such as COUNT, SUM, AVG, etc.
7. Question: How can you add a new record to a table?
Answer: Use the
INSERT INTO statement. For example: INSERT INTO table_name (column1, column2) VALUES (value1, value2);8. Question: What is the purpose of the HAVING clause?
Answer: The HAVING clause is used in combination with the GROUP BY clause to filter the results of aggregate functions based on a specified condition.
9. Question: Explain the concept of normalization in databases.
Answer: Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves breaking down tables into smaller, related tables.
10. Question: How do you update data in a table in SQL?
Answer: Use the
UPDATE statement to modify existing records in a table. For example: UPDATE table_name SET column1 = value1 WHERE condition;Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
❤6👏1
Getting started with SQL comparison operators.
If you're new to SQL, understanding comparison operators is one of the first things you'll need to learn.
They’re really important for filtering and analyzing your data. Let’s break them down with some simple examples.
Comparison operators let you compare values in SQL queries. Here are the basics:
1. = (Equal To): Checks if two values are the same.
Example: SELECT * FROM Employees WHERE Age = 30; (This will find all employees who are exactly 30 years old).
2. <> or != (Not Equal To): Checks if two values are different.
Example: SELECT * FROM Employees WHERE Age <> 30; (This will find all employees who are not 30 years old).
3. > (Greater Than): Checks if a value is larger.
Example: SELECT * FROM Employees WHERE Salary > 50000; (This will list all employees earning more than 50,000).
4. < (Less Than): Checks if a value is smaller.
Example: SELECT * FROM Employees WHERE Salary < 50000; (This will show all employees earning less than 50,000).
5. >= (Greater Than or Equal To): Checks if a value is larger or equal.
Example: SELECT * FROM Employees WHERE Age >= 25; (This will find all employees who are 25 years old or older).
6. <= (Less Than or Equal To): Checks if a value is smaller or equal.
Example: SELECT * FROM Employees WHERE Age <= 30; (This will find all employees who are 30 years old or younger).
These simple operators can help you get more accurate results in your SQL queries.
Keep practicing and you’ll be great at SQL in no time.
Like this post if you need more 👍❤️
Hope it helps :)
If you're new to SQL, understanding comparison operators is one of the first things you'll need to learn.
They’re really important for filtering and analyzing your data. Let’s break them down with some simple examples.
Comparison operators let you compare values in SQL queries. Here are the basics:
1. = (Equal To): Checks if two values are the same.
Example: SELECT * FROM Employees WHERE Age = 30; (This will find all employees who are exactly 30 years old).
2. <> or != (Not Equal To): Checks if two values are different.
Example: SELECT * FROM Employees WHERE Age <> 30; (This will find all employees who are not 30 years old).
3. > (Greater Than): Checks if a value is larger.
Example: SELECT * FROM Employees WHERE Salary > 50000; (This will list all employees earning more than 50,000).
4. < (Less Than): Checks if a value is smaller.
Example: SELECT * FROM Employees WHERE Salary < 50000; (This will show all employees earning less than 50,000).
5. >= (Greater Than or Equal To): Checks if a value is larger or equal.
Example: SELECT * FROM Employees WHERE Age >= 25; (This will find all employees who are 25 years old or older).
6. <= (Less Than or Equal To): Checks if a value is smaller or equal.
Example: SELECT * FROM Employees WHERE Age <= 30; (This will find all employees who are 30 years old or younger).
These simple operators can help you get more accurate results in your SQL queries.
Keep practicing and you’ll be great at SQL in no time.
Like this post if you need more 👍❤️
Hope it helps :)
❤7