SQL Zero to Hero ☝️

𝘚𝘘𝘓 𝘉𝘢𝘴𝘪𝘤𝘴 𝘧𝘰𝘳 𝘋𝘢𝘵𝘢 𝘚𝘤𝘪𝘦𝘯𝘵𝘪𝘴𝘵𝘴

𝘏𝘰𝘸 𝘸𝘦𝘭𝘭 𝘥𝘰 𝘺𝘰𝘶 𝘬𝘯𝘰𝘸 𝘚𝘘𝘓?

𝟏️⃣ 𝗦𝗘𝗟𝗘𝗖𝗧, 𝗪𝗛𝗘𝗥𝗘, 𝗮𝗻𝗱 𝗢𝗥𝗗𝗘𝗥 𝗕𝗬
⤷ Retrieve data from tables
⤷ Filter records with WHERE
⤷ Sort results using ORDER BY

𝟐️⃣ 𝗝𝗢𝗜𝗡𝗦 (𝗜𝗻𝗻𝗲𝗿, 𝗟𝗲𝗳𝘁, 𝗥𝗶𝗴𝗵𝘁, 𝗙𝘂𝗹𝗹)
⤷ Combine data from multiple tables
⤷ Use INNER JOIN for common records
⤷ Use LEFT JOIN to keep all left table records

𝟑️⃣ 𝗔𝗚𝗚𝗥𝗘𝗚𝗔𝗧𝗜𝗢𝗡 (𝗖𝗢𝗨𝗡𝗧, 𝗦𝗨𝗠, 𝗔𝗩𝗚, 𝗠𝗔𝗫, 𝗠𝗜𝗡)
⤷ Summarize and analyze data
⤷ Use GROUP BY for grouped metrics
⤷ Filter groups with HAVING

𝟒️⃣ 𝗦𝗨𝗕𝗤𝗨𝗘𝗥𝗜𝗘𝗦 𝗮𝗻𝗱 𝗖𝗧𝗘𝘀
⤷ Nested queries for advanced filtering
⤷ WITH clause to improve readability

𝟓️⃣ 𝗪𝗜𝗡𝗗𝗢𝗪 𝗙𝗨𝗡𝗖𝗧𝗜𝗢𝗡𝗦
⤷ Use RANK(), DENSE_RANK(), ROW_NUMBER()
⤷ Analyze running totals and moving averages

𝟔️⃣ 𝗘𝗙𝗙𝗜𝗖𝗜𝗘𝗡𝗖𝗬 𝗪𝗜𝗧𝗛 𝗜𝗡𝗗𝗘𝗫𝗘𝗦
⤷ Speed up queries using indexing
⤷ Understand clustered vs. non-clustered indexes

🔗 𝘓𝘦𝘢𝘳𝘯 𝘚𝘘𝘓 𝘍𝘙𝘌𝘌 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦𝘴𝘦 𝘳𝘦𝘴𝘰𝘶𝘳𝘤𝘦𝘴:
⤷ 𝘞𝟹𝘚𝘤𝘩𝘰𝘰𝘭𝘴 - w3schools.com/sql/
⤷ Interviews - t.iss.one/mysqldata

𝘕𝘦𝘹𝘵 𝘵𝘪𝘮𝘦 𝘴𝘰𝘮𝘦𝘰𝘯𝘦 𝘢𝘴𝘬𝘴, “𝘋𝘰 𝘺𝘰𝘶 𝘬𝘯𝘰𝘸 𝘚𝘘𝘓?” 𝘠𝘰𝘶’𝘭𝘭 𝘩𝘢𝘷𝘦 𝘵𝘩𝘦 𝘢𝘯𝘴𝘸𝘦𝘳.

SQL CHEAT SHEET👩‍💻

SQL is a language used to communicate with databases it stands for Structured Query Language and is used by database administrators and developers alike to write queries that are used to interact with the database. Here is a quick cheat sheet of some of the most essential SQL commands:

SELECT - Retrieves data from a database

UPDATE - Updates existing data in a database

DELETE - Removes data from a database

INSERT - Adds data to a database

CREATE - Creates an object such as a database or table

ALTER - Modifies an existing object in a database

DROP -Deletes an entire table or database

ORDER BY - Sorts the selected data in an ascending or descending order

WHERE – Condition used to filter a specific set of records from the database

GROUP BY - Groups a set of data by a common parameter

HAVING - Allows the use of aggregate functions within the query

JOIN - Joins two or more tables together to retrieve data

INDEX - Creates an index on a table, to speed up search times.

Here you can find essential SQL Interview Resources👇
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Here are few Important SQL interview questions with topics

Basic SQL Concepts:

Explain the difference between SQL and NoSQL databases.
What are the common data types in SQL?

Querying:

How do you retrieve all records from a table named "Customers"?
What is the difference between SELECT and SELECT DISTINCT in a query?
Explain the purpose of the WHERE clause in SQL queries.

Joins:
Describe the types of joins in SQL (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN).
How would you retrieve data from two tables using an INNER JOIN?

Aggregate Functions:
What are aggregate functions in SQL? Can you name a few?
How do you calculate the average, sum, and count of a column in a SQL query?

Grouping and Filtering:
Explain the GROUP BY clause and its use in SQL.
How would you filter the results of an SQL query using the HAVING clause?

Subqueries:
What is a subquery, and when would you use one in SQL?
Provide an example of a subquery in an SQL statement.

Indexes and Optimization:
Why are indexes important in a database?
How would you optimize a slow-running SQL query?

Normalization and Data Integrity:
What is database normalization, and why is it important?
How can you enforce data integrity in a SQL database?

Transactions:
What is a SQL transaction, and why would you use it?
Explain the concepts of ACID properties in database transactions.

Views and Stored Procedures:
What is a database view, and when would you create one?
What is a stored procedure, and how does it differ from a regular SQL query?

Advanced SQL:
Can you write a recursive SQL query, and when would you use recursion?
Explain the concept of window functions in SQL.

These questions cover a range of SQL topics, from basic concepts to more advanced techniques, and can help assess a candidate's knowledge and skills in SQL :)

Here you can find essential SQL Interview Resources👇
https://t.iss.one/mysqldata

Like this post if you need more 👍❤️

Hope it helps :)

SQL, or Structured Query Language, is a domain-specific language used to manage and manipulate relational databases. Here's a brief A-Z overview by @sqlanalyst

A - Aggregate Functions: Functions like COUNT, SUM, AVG, MIN, and MAX used to perform operations on data in a database.

B - BETWEEN: A SQL operator used to filter results within a specific range.

C - CREATE TABLE: SQL statement for creating a new table in a database.

D - DELETE: SQL statement used to delete records from a table.

E - EXISTS: SQL operator used in a subquery to test if a specified condition exists.

F - FOREIGN KEY: A field in a database table that is a primary key in another table, establishing a link between the two tables.

G - GROUP BY: SQL clause used to group rows that have the same values in specified columns.

H - HAVING: SQL clause used in combination with GROUP BY to filter the results.

I - INNER JOIN: SQL clause used to combine rows from two or more tables based on a related column between them.

J - JOIN: Combines rows from two or more tables based on a related column.

K - KEY: A field or set of fields in a database table that uniquely identifies each record.

L - LIKE: SQL operator used in a WHERE clause to search for a specified pattern in a column.

M - MODIFY: SQL command used to modify an existing database table.

N - NULL: Represents missing or undefined data in a database.

O - ORDER BY: SQL clause used to sort the result set in ascending or descending order.

P - PRIMARY KEY: A field in a table that uniquely identifies each record in that table.

Q - QUERY: A request for data from a database using SQL.

R - ROLLBACK: SQL command used to undo transactions that have not been saved to the database.

S - SELECT: SQL statement used to query the database and retrieve data.

T - TRUNCATE: SQL command used to delete all records from a table without logging individual row deletions.

U - UPDATE: SQL statement used to modify the existing records in a table.

V - VIEW: A virtual table based on the result of a SELECT query.

W - WHERE: SQL clause used to filter the results of a query based on a specified condition.

X - (E)XISTS: Used in conjunction with SELECT to test the existence of rows returned by a subquery.

Z - ZERO: Represents the absence of a value in numeric fields or the initial state of boolean fields.

The Secret to learn SQL:
It's not about knowing everything
It's about doing simple things well

What You ACTUALLY Need:

1. SELECT Mastery

* SELECT * LIMIT 10
(yes, for exploration only!)
* COUNT, SUM, AVG
(used every single day)
* Basic DATE functions
(life-saving for reports)
* CASE WHEN

2. JOIN Logic

* LEFT JOIN
(your best friend)
* INNER JOIN
(your second best friend)
* That's it.

3. WHERE Magic
* Basic conditions
* AND, OR operators
* IN, NOT IN
* NULL handling
* LIKE for text search

4. GROUP BY Essentials
* Basic grouping
* HAVING clause
* Multiple columns
* Simple aggregations

Most common tasks:
* Pull monthly sales
* Count unique customers
* Calculate basic metrics
* Filter date ranges
* Join 2-3 tables

Focus on:
* Clean code
* Clear comments
* Consistent formatting
* Proper indentation

Here you can find essential SQL Interview Resources👇
https://t.iss.one/mysqldata

Like this post if you need more 👍❤️

Hope it helps :)

#sql

The GROUP BY clause in SQL is used to arrange identical data into groups. This is particularly useful when combined with aggregate functions like COUNT(), SUM(), AVG(), MIN(), and MAX(). The GROUP BY clause groups rows that have the same values in specified columns into summary rows.

▎Basic Syntax

SELECT column1, aggregate_function(column2)
FROM table_name
WHERE condition
GROUP BY column1;

▎Example 1: Counting Rows

Suppose you have a table called employees with the following structure:

| id | department | salary |
|----|------------|--------|
| 1 | HR | 50000 |
| 2 | IT | 60000 |
| 3 | HR | 55000 |
| 4 | IT | 70000 |
| 5 | Sales | 65000 |

To find out how many employees are in each department, you can use:

SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department;

Result:

| department | employee_count |
|------------|----------------|
| HR | 2 |
| IT | 2 |
| Sales | 1 |

▎Example 2: Summing Salaries

To calculate the total salary paid to employees in each department, you can use:

SELECT department, SUM(salary) AS total_salary
FROM employees
GROUP BY department;

Result:

| department | total_salary |
|------------|--------------|
| HR | 105000 |
| IT | 130000 |
| Sales | 65000 |

▎Example 3: Average Salary

To find the average salary of employees in each department:

SELECT department, AVG(salary) AS average_salary
FROM employees
GROUP BY department;

Result:

| department | average_salary |
|------------|----------------|
| HR | 52500 |
| IT | 65000 |
| Sales | 65000 |

▎Example 4: Grouping by Multiple Columns

You can also group by multiple columns. For instance, if you had another column for job_title:

| id | department | job_title | salary |
|----|------------|-----------|--------|
| 1 | HR | Manager | 50000 |
| 2 | IT | Developer | 60000 |
| 3 | HR | Assistant | 55000 |
| 4 | IT | Manager | 70000 |
| 5 | Sales | Executive | 65000 |

To count employees by both department and job_title:

SELECT department, job_title, COUNT(*) AS employee_count
FROM employees
GROUP BY department, job_title;

Result:

| department | job_title | employee_count |
|------------|-----------|----------------|
| HR | Manager | 1 |
| HR | Assistant | 1 |
| IT | Developer | 1 |
| IT | Manager | 1 |
| Sales | Executive | 1 |

▎Important Notes

1. Aggregate Functions: Any column in the SELECT statement that is not an aggregate function must be included in the GROUP BY clause.

2. HAVING Clause: You can filter groups using the HAVING clause, which is similar to the WHERE clause but is used for aggregated data. For example:

   SELECT department, COUNT(*) AS employee_count
   FROM employees
   GROUP BY department
   HAVING COUNT(*) > 1;
   

This would return only departments with more than one employee.

▎Conclusion

The GROUP BY clause is a powerful tool in SQL for summarizing data. It allows you to analyze and report on your datasets effectively by grouping similar data points and applying aggregate functions.