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.
Theyโre really important for filtering and analyzing your data. Letโs 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 youโll be great at SQL in no time.
Like this post if you need more ๐โค๏ธ
Hope it helps :)
If you're new to SQL, understanding comparison operators is one of the first things you'll need to learn.
Theyโre really important for filtering and analyzing your data. Letโs 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 youโll be great at SQL in no time.
Like this post if you need more ๐โค๏ธ
Hope it helps :)
๐3โค2
SQL is one of the core languages used in data science, powering everything from quick data retrieval to complex deep dive analysis. Whether you're a seasoned data scientist or just starting out, mastering SQL can boost your ability to analyze data, create robust pipelines, and deliver actionable insights.
Letโs dive into a comprehensive guide on SQL for Data Science!
I have broken it down into three key sections to help you:
๐ญ. ๐ฆ๐ค๐ ๐๐ผ๐ป๐ฐ๐ฒ๐ฝ๐๐:
Get a handle on the essentials -> SELECT statements, filtering, aggregations, joins, window functions, and more.
๐ฎ. ๐ฆ๐ค๐ ๐ถ๐ป ๐๐ฎ๐-๐๐ผ-๐๐ฎ๐ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ:
See how SQL fits into the daily data science workflow. From quick data queries and deep-dive analysis to building pipelines and dashboards, SQL is really useful for data scientists, especially for product data scientists.
๐ฏ. ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ฆ๐ค๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐:
Learn what interviewers look for in terms of technical skills, design and engineering expertise, communication abilities, and the importance of speed and accuracy.
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
#sql
Letโs dive into a comprehensive guide on SQL for Data Science!
I have broken it down into three key sections to help you:
๐ญ. ๐ฆ๐ค๐ ๐๐ผ๐ป๐ฐ๐ฒ๐ฝ๐๐:
Get a handle on the essentials -> SELECT statements, filtering, aggregations, joins, window functions, and more.
๐ฎ. ๐ฆ๐ค๐ ๐ถ๐ป ๐๐ฎ๐-๐๐ผ-๐๐ฎ๐ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ:
See how SQL fits into the daily data science workflow. From quick data queries and deep-dive analysis to building pipelines and dashboards, SQL is really useful for data scientists, especially for product data scientists.
๐ฏ. ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ฆ๐ค๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐๐:
Learn what interviewers look for in terms of technical skills, design and engineering expertise, communication abilities, and the importance of speed and accuracy.
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
#sql
๐2โค1
Preparing for a SQL interview?
Focus on mastering these essential topics:
1. Joins: Get comfortable with inner, left, right, and outer joins.
Knowing when to use what kind of join is important!
2. Window Functions: Understand when to use
ROW_NUMBER, RANK(), DENSE_RANK(), LAG, and LEAD for complex analytical queries.
3. Query Execution Order: Know the sequence from FROM to
ORDER BY. This is crucial for writing efficient, error-free queries.
4. Common Table Expressions (CTEs): Use CTEs to simplify and structure complex queries for better readability.
5. Aggregations & Window Functions: Combine aggregate functions with window functions for in-depth data analysis.
6. Subqueries: Learn how to use subqueries effectively within main SQL statements for complex data manipulations.
7. Handling NULLs: Be adept at managing NULL values to ensure accurate data processing and avoid potential pitfalls.
8. Indexing: Understand how proper indexing can significantly boost query performance.
9. GROUP BY & HAVING: Master grouping data and filtering groups with HAVING to refine your query results.
10. String Manipulation Functions: Get familiar with string functions like CONCAT, SUBSTRING, and REPLACE to handle text data efficiently.
11. Set Operations: Know how to use UNION, INTERSECT, and EXCEPT to combine or compare result sets.
12. Optimizing Queries: Learn techniques to optimize your queries for performance, especially with large datasets.
If we master/ Practice in these topics we can track any SQL interviews..
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
Focus on mastering these essential topics:
1. Joins: Get comfortable with inner, left, right, and outer joins.
Knowing when to use what kind of join is important!
2. Window Functions: Understand when to use
ROW_NUMBER, RANK(), DENSE_RANK(), LAG, and LEAD for complex analytical queries.
3. Query Execution Order: Know the sequence from FROM to
ORDER BY. This is crucial for writing efficient, error-free queries.
4. Common Table Expressions (CTEs): Use CTEs to simplify and structure complex queries for better readability.
5. Aggregations & Window Functions: Combine aggregate functions with window functions for in-depth data analysis.
6. Subqueries: Learn how to use subqueries effectively within main SQL statements for complex data manipulations.
7. Handling NULLs: Be adept at managing NULL values to ensure accurate data processing and avoid potential pitfalls.
8. Indexing: Understand how proper indexing can significantly boost query performance.
9. GROUP BY & HAVING: Master grouping data and filtering groups with HAVING to refine your query results.
10. String Manipulation Functions: Get familiar with string functions like CONCAT, SUBSTRING, and REPLACE to handle text data efficiently.
11. Set Operations: Know how to use UNION, INTERSECT, and EXCEPT to combine or compare result sets.
12. Optimizing Queries: Learn techniques to optimize your queries for performance, especially with large datasets.
If we master/ Practice in these topics we can track any SQL interviews..
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
โค1๐1
๐๐จ๐ฆ๐ ๐๐๐ฌ๐ญ ๐ฉ๐ซ๐๐๐ญ๐ข๐๐๐ฌ ๐ญ๐จ ๐ก๐๐ฅ๐ฉ ๐ฒ๐จ๐ฎ ๐จ๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐ ๐ฒ๐จ๐ฎ๐ซ ๐๐๐ ๐ช๐ฎ๐๐ซ๐ข๐๐ฌ:
1. Simplify Joins
โข Decompose complex joins into simpler, more manageable queries when possible.
โข Index columns that are used as foreign keys in joins to enhance join performance.
2. Query Structure Optimization
โข Apply WHERE clauses as early as possible to filter out rows before they are processed further.
โข Utilize LIMIT or TOP clauses to restrict the number of rows returned, which can significantly reduce processing time.
3. Partition Large Tables
โข Divide large tables into smaller, more manageable partitions.
โข Ensure that each partition is properly indexed to maintain query performance.
4. Optimize SELECT Statements
โข Limit the columns in your SELECT clause to only those you need. Avoid using SELECT * to prevent unnecessary data retrieval.
โข Prefer using EXISTS over IN for subqueries to improve query performance.
5. Use Temporary Tables Wisely
โข Temporary Tables: Use temporary tables to save intermediate results when you have a complex query. This helps break down a complicated query into simpler steps, making it easier to manage and faster to run.
6. Optimize Table Design
โข Normalize your database schema to eliminate redundant data and improve consistency.
โข Consider denormalization for read-heavy systems to reduce the number of joins needed.
7. Avoid Correlated Subqueries
โข Replace correlated subqueries with joins or use derived tables to improve performance.
โข Correlated subqueries can be very inefficient as they are executed multiple times.
8. Use Stored Procedures:
โข Put complicated database tasks into stored procedures. These are pre-written sets of instructions saved in the database. They make your queries run faster because the database doesnโt have to figure out how to execute them each time
SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
1. Simplify Joins
โข Decompose complex joins into simpler, more manageable queries when possible.
โข Index columns that are used as foreign keys in joins to enhance join performance.
2. Query Structure Optimization
โข Apply WHERE clauses as early as possible to filter out rows before they are processed further.
โข Utilize LIMIT or TOP clauses to restrict the number of rows returned, which can significantly reduce processing time.
3. Partition Large Tables
โข Divide large tables into smaller, more manageable partitions.
โข Ensure that each partition is properly indexed to maintain query performance.
4. Optimize SELECT Statements
โข Limit the columns in your SELECT clause to only those you need. Avoid using SELECT * to prevent unnecessary data retrieval.
โข Prefer using EXISTS over IN for subqueries to improve query performance.
5. Use Temporary Tables Wisely
โข Temporary Tables: Use temporary tables to save intermediate results when you have a complex query. This helps break down a complicated query into simpler steps, making it easier to manage and faster to run.
6. Optimize Table Design
โข Normalize your database schema to eliminate redundant data and improve consistency.
โข Consider denormalization for read-heavy systems to reduce the number of joins needed.
7. Avoid Correlated Subqueries
โข Replace correlated subqueries with joins or use derived tables to improve performance.
โข Correlated subqueries can be very inefficient as they are executed multiple times.
8. Use Stored Procedures:
โข Put complicated database tasks into stored procedures. These are pre-written sets of instructions saved in the database. They make your queries run faster because the database doesnโt have to figure out how to execute them each time
SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
๐2โค1
A lot of people struggle with SQL Joins.
The truth is, once you've grasped it, you won't forget it.
Here's my super simple breakdown of common SQL joins:
To start, let's quickly cover what a join is in SQL.
Data can be stored in RDMS which means relational database management systems.
Being relational indicates data in tables can relate to each other.
To relate data we need to join it.
When working with data, there are 2 types of joins that you will use more than any other.
Let's get into it...
For this post let's pretend we have 2 tables: table 1 and table 2.
Join 1: Left join
Left join simply means we take all rows from table 1 and look at table 2 for any matches based on a field (or fields).
If there is a match, we return every row from table 1 with the matching row from table 2. If there is no match the result from table 2 will be NULL.
Join 2: Inner join
Now, let's look at the inner join.
Inner join identifies and selects records that have matching values in both tables.
Picture it like a Venn diagram, where only the overlapping area, representing the common values, is selected.
This means that if there's no match between the tables based on the specified fields, those rows won't be included in the result set.
Remember left join returns ALL rows from table 1 so the number of rows wont change pre vs post join (assuming no duplicate values).
With inner join this is slightly different, the number of rows CAN change because we are only looking for matches in both tables.
And there you have it, my super simple breakdown of the most common SQL joins.
If you learned something from this, give this post a like
The truth is, once you've grasped it, you won't forget it.
Here's my super simple breakdown of common SQL joins:
To start, let's quickly cover what a join is in SQL.
Data can be stored in RDMS which means relational database management systems.
Being relational indicates data in tables can relate to each other.
To relate data we need to join it.
When working with data, there are 2 types of joins that you will use more than any other.
Let's get into it...
For this post let's pretend we have 2 tables: table 1 and table 2.
Join 1: Left join
Left join simply means we take all rows from table 1 and look at table 2 for any matches based on a field (or fields).
If there is a match, we return every row from table 1 with the matching row from table 2. If there is no match the result from table 2 will be NULL.
Join 2: Inner join
Now, let's look at the inner join.
Inner join identifies and selects records that have matching values in both tables.
Picture it like a Venn diagram, where only the overlapping area, representing the common values, is selected.
This means that if there's no match between the tables based on the specified fields, those rows won't be included in the result set.
Remember left join returns ALL rows from table 1 so the number of rows wont change pre vs post join (assuming no duplicate values).
With inner join this is slightly different, the number of rows CAN change because we are only looking for matches in both tables.
And there you have it, my super simple breakdown of the most common SQL joins.
If you learned something from this, give this post a like
๐9๐2โค1
Top interview SQL questions, including both technical and non-technical questions, along with their answers PART-1
1. What is SQL?
- Answer: SQL (Structured Query Language) is a standard programming language specifically designed for managing and manipulating relational databases.
2. What are the different types of SQL statements?
- Answer: SQL statements can be classified into DDL (Data Definition Language), DML (Data Manipulation Language), DCL (Data Control Language), and TCL (Transaction Control Language).
3. What is a primary key?
- Answer: A primary key is a field (or combination of fields) in a table that uniquely identifies each row/record in that table.
4. What is a foreign key?
- Answer: A foreign key is a field (or collection of fields) in one table that uniquely identifies a row of another table or the same table. It establishes a link between the data in two tables.
5. What are joins? Explain different types of joins.
- Answer: A join is an SQL operation for combining records from two or more tables. Types of joins include INNER JOIN, LEFT JOIN (or LEFT OUTER JOIN), RIGHT JOIN (or RIGHT OUTER JOIN), and FULL JOIN (or FULL OUTER JOIN).
6. What is normalization?
- Answer: Normalization is the process of organizing data to reduce redundancy and improve data integrity. This typically involves dividing a database into two or more tables and defining relationships between them.
7. What is denormalization?
- Answer: Denormalization is the process of combining normalized tables into fewer tables to improve database read performance, sometimes at the expense of write performance and data integrity.
8. What is stored procedure?
- Answer: A stored procedure is a prepared SQL code that you can save and reuse. So, if you have an SQL query that you write frequently, you can save it as a stored procedure and then call it to execute it.
9. What is an index?
- Answer: An index is a database object that improves the speed of data retrieval operations on a table at the cost of additional storage and maintenance overhead.
10. What is a view in SQL?
- Answer: A view is a virtual table based on the result set of an SQL query. It contains rows and columns, just like a real table, but does not physically store the data.
11. What is a subquery?
- Answer: A subquery is an SQL query nested inside a larger query. It is used to return data that will be used in the main query as a condition to further restrict the data to be retrieved.
12. What are aggregate functions in SQL?
- Answer: Aggregate functions perform a calculation on a set of values and return a single value. Examples include COUNT, SUM, AVG (average), MIN (minimum), and MAX (maximum).
13. Difference between DELETE and TRUNCATE?
- Answer: DELETE removes rows one at a time and logs each delete, while TRUNCATE removes all rows in a table without logging individual row deletions. TRUNCATE is faster but cannot be rolled back.
14. What is a UNION in SQL?
- Answer: UNION is an operator used to combine the result sets of two or more SELECT statements. It removes duplicate rows between the various SELECT statements.
15. What is a cursor in SQL?
- Answer: A cursor is a database object used to retrieve, manipulate, and navigate through a result set one row at a time.
16. What is trigger in SQL?
- Answer: A trigger is a set of SQL statements that automatically execute or "trigger" when certain events occur in a database, such as INSERT, UPDATE, or DELETE.
17. Difference between clustered and non-clustered indexes?
- Answer: A clustered index determines the physical order of data in a table and can only be one per table. A non-clustered index, on the other hand, creates a logical order and can be many per table.
18. Explain the term ACID.
- Answer: ACID stands for Atomicity, Consistency, Isolation, and Durability.
SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Hope it helps :)
1. What is SQL?
- Answer: SQL (Structured Query Language) is a standard programming language specifically designed for managing and manipulating relational databases.
2. What are the different types of SQL statements?
- Answer: SQL statements can be classified into DDL (Data Definition Language), DML (Data Manipulation Language), DCL (Data Control Language), and TCL (Transaction Control Language).
3. What is a primary key?
- Answer: A primary key is a field (or combination of fields) in a table that uniquely identifies each row/record in that table.
4. What is a foreign key?
- Answer: A foreign key is a field (or collection of fields) in one table that uniquely identifies a row of another table or the same table. It establishes a link between the data in two tables.
5. What are joins? Explain different types of joins.
- Answer: A join is an SQL operation for combining records from two or more tables. Types of joins include INNER JOIN, LEFT JOIN (or LEFT OUTER JOIN), RIGHT JOIN (or RIGHT OUTER JOIN), and FULL JOIN (or FULL OUTER JOIN).
6. What is normalization?
- Answer: Normalization is the process of organizing data to reduce redundancy and improve data integrity. This typically involves dividing a database into two or more tables and defining relationships between them.
7. What is denormalization?
- Answer: Denormalization is the process of combining normalized tables into fewer tables to improve database read performance, sometimes at the expense of write performance and data integrity.
8. What is stored procedure?
- Answer: A stored procedure is a prepared SQL code that you can save and reuse. So, if you have an SQL query that you write frequently, you can save it as a stored procedure and then call it to execute it.
9. What is an index?
- Answer: An index is a database object that improves the speed of data retrieval operations on a table at the cost of additional storage and maintenance overhead.
10. What is a view in SQL?
- Answer: A view is a virtual table based on the result set of an SQL query. It contains rows and columns, just like a real table, but does not physically store the data.
11. What is a subquery?
- Answer: A subquery is an SQL query nested inside a larger query. It is used to return data that will be used in the main query as a condition to further restrict the data to be retrieved.
12. What are aggregate functions in SQL?
- Answer: Aggregate functions perform a calculation on a set of values and return a single value. Examples include COUNT, SUM, AVG (average), MIN (minimum), and MAX (maximum).
13. Difference between DELETE and TRUNCATE?
- Answer: DELETE removes rows one at a time and logs each delete, while TRUNCATE removes all rows in a table without logging individual row deletions. TRUNCATE is faster but cannot be rolled back.
14. What is a UNION in SQL?
- Answer: UNION is an operator used to combine the result sets of two or more SELECT statements. It removes duplicate rows between the various SELECT statements.
15. What is a cursor in SQL?
- Answer: A cursor is a database object used to retrieve, manipulate, and navigate through a result set one row at a time.
16. What is trigger in SQL?
- Answer: A trigger is a set of SQL statements that automatically execute or "trigger" when certain events occur in a database, such as INSERT, UPDATE, or DELETE.
17. Difference between clustered and non-clustered indexes?
- Answer: A clustered index determines the physical order of data in a table and can only be one per table. A non-clustered index, on the other hand, creates a logical order and can be many per table.
18. Explain the term ACID.
- Answer: ACID stands for Atomicity, Consistency, Isolation, and Durability.
SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Hope it helps :)
๐10โค2
SQL can be simpleโif you learn it the smart way..
If youโre aiming to become a data analyst, mastering SQL is non-negotiable.
Hereโs 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! ๐ช
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
If youโre aiming to become a data analyst, mastering SQL is non-negotiable.
Hereโs 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! ๐ช
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
๐6
Essential SQL Topics for Data Analyst
Introduction to Databases
Fundamentals of databases and Database Management Systems (DBMS)
Basic SQL syntax and structure
Retrieving Data
Using the SELECT statement
Filtering data with the WHERE clause
Sorting results using ORDER BY
Limiting output with LIMIT (MySQL) or TOP (SQL Server)
Basic SQL Functions
Utilizing COUNT, SUM, AVG, MIN, and MAX
Data Types
Numeric, character, date, and time data types
Joining Tables
INNER JOIN
LEFT JOIN (or LEFT OUTER JOIN)
RIGHT JOIN (or RIGHT OUTER JOIN)
FULL JOIN (or FULL OUTER JOIN)
CROSS JOIN
Self JOIN
Advanced Data Filtering
Using IN and NOT IN
Applying BETWEEN for range filtering
Using LIKE with wildcards
Handling NULL values with IS NULL and IS NOT NULL
Grouping and Aggregation
GROUP BY clause
Filtering groups with HAVING
Subqueries
Subqueries in the SELECT clause
Subqueries in the WHERE clause
Derived tables using subqueries in the FROM clause
Correlated subqueries
Set Operations
Combining results with UNION
UNION ALL for combining results including duplicates
INTERSECT for common elements
EXCEPT (or MINUS) for differences
Window Functions
Using ROW_NUMBER
RANK and DENSE_RANK
NTILE for distributing rows
LEAD and LAG for accessing prior or subsequent rows
Aggregate functions as window functions (SUM, AVG, COUNT)
Common Table Expressions (CTEs)
Using the WITH clause
Creating recursive CTEs
Stored Procedures and Functions
Creating and utilizing stored procedures
Creating and utilizing user-defined functions
Views
Creating and managing views
Using indexed views (materialized views)
Indexing
Creating indexes
Understanding clustered versus non-clustered indexes
Maintaining indexes
Transactions
Controlling transactions with BEGIN, COMMIT, and ROLLBACK
Performance Optimization
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
Introduction to Databases
Fundamentals of databases and Database Management Systems (DBMS)
Basic SQL syntax and structure
Retrieving Data
Using the SELECT statement
Filtering data with the WHERE clause
Sorting results using ORDER BY
Limiting output with LIMIT (MySQL) or TOP (SQL Server)
Basic SQL Functions
Utilizing COUNT, SUM, AVG, MIN, and MAX
Data Types
Numeric, character, date, and time data types
Joining Tables
INNER JOIN
LEFT JOIN (or LEFT OUTER JOIN)
RIGHT JOIN (or RIGHT OUTER JOIN)
FULL JOIN (or FULL OUTER JOIN)
CROSS JOIN
Self JOIN
Advanced Data Filtering
Using IN and NOT IN
Applying BETWEEN for range filtering
Using LIKE with wildcards
Handling NULL values with IS NULL and IS NOT NULL
Grouping and Aggregation
GROUP BY clause
Filtering groups with HAVING
Subqueries
Subqueries in the SELECT clause
Subqueries in the WHERE clause
Derived tables using subqueries in the FROM clause
Correlated subqueries
Set Operations
Combining results with UNION
UNION ALL for combining results including duplicates
INTERSECT for common elements
EXCEPT (or MINUS) for differences
Window Functions
Using ROW_NUMBER
RANK and DENSE_RANK
NTILE for distributing rows
LEAD and LAG for accessing prior or subsequent rows
Aggregate functions as window functions (SUM, AVG, COUNT)
Common Table Expressions (CTEs)
Using the WITH clause
Creating recursive CTEs
Stored Procedures and Functions
Creating and utilizing stored procedures
Creating and utilizing user-defined functions
Views
Creating and managing views
Using indexed views (materialized views)
Indexing
Creating indexes
Understanding clustered versus non-clustered indexes
Maintaining indexes
Transactions
Controlling transactions with BEGIN, COMMIT, and ROLLBACK
Performance Optimization
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SQL Interview Questions! ๐ฅ๐
Basic SQL Interview Questions:
- What is SQL?
- What are the different types of SQL commands?
- What is the difference between DDL, DML, DCL, and TCL?
- What is the difference between SQL and MySQL?
- What is a primary key?
- What is a foreign key?
- What is a unique key?
- What is the difference between primary key and unique key?
- What is the difference between HAVING and WHERE?
- What are constraints in SQL? Name a few.
- What is the difference between CHAR and VARCHAR?
- What is Normalization? What are its types?
- What is Denormalization?
- What is an index in SQL?
- What are the different types of indexes?
- What is the difference between Clustered and Non-clustered indexes?
- What is an alias in SQL?
- What is the difference between DELETE and TRUNCATE?
- What is the difference between TRUNCATE and DROP?
- What is a view in SQL?
-------------------------------------
Intermediate SQL Interview Questions:
What is a self-join?
What is an inner join?
What is the difference between INNER JOIN and OUTER JOIN?
What are the types of OUTER JOIN?
What is a cross join?
What is a Cartesian join?
What is the difference between UNION and UNION ALL?
What is the difference between JOIN and UNION?
What is a stored procedure?
What is a trigger in SQL?
What are the different types of triggers?
What is the difference between HAVING and GROUP BY?
What are subqueries?
What are correlated subqueries?
What is an EXISTS clause in SQL?
What is the difference between EXISTS and IN?
What is a cursor in SQL?
What is the difference between OLTP and OLAP?
What are ACID properties in SQL?
What is normalization? Explain 1NF, 2NF, 3NF, and BCNF.
What is a composite key?
What is a surrogate key?
What is the use of the COALESCE function?
What is the difference between IS
NULL and IS NOT NULL?
What is partitioning in SQL?
-------------------------------------
Advanced SQL Interview Questions:
What are window functions in SQL?
What is CTE (Common Table Expression)?
What is the difference between TEMP TABLE and CTE?
What is the difference between RANK(), DENSE_RANK(), and ROW_NUMBER()?
What is a materialized view?
What is the difference between materialized views and normal views?
What is sharding in SQL?
What is the MERGE statement?
What is the JSON data type in SQL?
What is recursive CTE?
What is the difference between LEFT JOIN and LEFT OUTER JOIN?
How does indexing impact performance?
What is the difference between OLAP and OLTP?
What is ETL (Extract, Transform, Load)?
What are window functions? Explain LEAD, LAG, and NTILE.
What is a pivot table in SQL?
What is Dynamic SQL?
What is a NoSQL database? How is it different from SQL databases?
What is the difference between SQL and PL/SQL?
How to find the N-th highest salary in SQL?
-------------------------------------
Practical SQL Queries:
Find the second highest salary from an Employee table.
Find duplicate records in a table.
Write a SQL query to find the count of employees in each department.
Write a query to find employees who earn more than their managers.
Write a query to fetch the first three characters of a string.
Write a SQL query to swap two columns in a table without using a temporary table.
Write a query to find all employees who joined in the last 6 months.
Write a query to find the most repeated values in a column.
Write a query to delete duplicate rows from a table.
Write a SQL query to find all customers who made more than 5 purchases.
React โฅ๏ธ for more content like this ๐
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
Basic SQL Interview Questions:
- What is SQL?
- What are the different types of SQL commands?
- What is the difference between DDL, DML, DCL, and TCL?
- What is the difference between SQL and MySQL?
- What is a primary key?
- What is a foreign key?
- What is a unique key?
- What is the difference between primary key and unique key?
- What is the difference between HAVING and WHERE?
- What are constraints in SQL? Name a few.
- What is the difference between CHAR and VARCHAR?
- What is Normalization? What are its types?
- What is Denormalization?
- What is an index in SQL?
- What are the different types of indexes?
- What is the difference between Clustered and Non-clustered indexes?
- What is an alias in SQL?
- What is the difference between DELETE and TRUNCATE?
- What is the difference between TRUNCATE and DROP?
- What is a view in SQL?
-------------------------------------
Intermediate SQL Interview Questions:
What is a self-join?
What is an inner join?
What is the difference between INNER JOIN and OUTER JOIN?
What are the types of OUTER JOIN?
What is a cross join?
What is a Cartesian join?
What is the difference between UNION and UNION ALL?
What is the difference between JOIN and UNION?
What is a stored procedure?
What is a trigger in SQL?
What are the different types of triggers?
What is the difference between HAVING and GROUP BY?
What are subqueries?
What are correlated subqueries?
What is an EXISTS clause in SQL?
What is the difference between EXISTS and IN?
What is a cursor in SQL?
What is the difference between OLTP and OLAP?
What are ACID properties in SQL?
What is normalization? Explain 1NF, 2NF, 3NF, and BCNF.
What is a composite key?
What is a surrogate key?
What is the use of the COALESCE function?
What is the difference between IS
NULL and IS NOT NULL?
What is partitioning in SQL?
-------------------------------------
Advanced SQL Interview Questions:
What are window functions in SQL?
What is CTE (Common Table Expression)?
What is the difference between TEMP TABLE and CTE?
What is the difference between RANK(), DENSE_RANK(), and ROW_NUMBER()?
What is a materialized view?
What is the difference between materialized views and normal views?
What is sharding in SQL?
What is the MERGE statement?
What is the JSON data type in SQL?
What is recursive CTE?
What is the difference between LEFT JOIN and LEFT OUTER JOIN?
How does indexing impact performance?
What is the difference between OLAP and OLTP?
What is ETL (Extract, Transform, Load)?
What are window functions? Explain LEAD, LAG, and NTILE.
What is a pivot table in SQL?
What is Dynamic SQL?
What is a NoSQL database? How is it different from SQL databases?
What is the difference between SQL and PL/SQL?
How to find the N-th highest salary in SQL?
-------------------------------------
Practical SQL Queries:
Find the second highest salary from an Employee table.
Find duplicate records in a table.
Write a SQL query to find the count of employees in each department.
Write a query to find employees who earn more than their managers.
Write a query to fetch the first three characters of a string.
Write a SQL query to swap two columns in a table without using a temporary table.
Write a query to find all employees who joined in the last 6 months.
Write a query to find the most repeated values in a column.
Write a query to delete duplicate rows from a table.
Write a SQL query to find all customers who made more than 5 purchases.
React โฅ๏ธ for more content like this ๐
Here you can find essential SQL Interview Resources๐
https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Like this post if you need more ๐โค๏ธ
Hope it helps :)
๐11โค1