SQL Functions

If you are interested to learn SQL for data analytics purpose and clear the interviews, just cover the following topics 📚

1. Install MYSQL workbench 💻
2. Select 📈
3. From 📁
4. where 🔍
5. group by 📊
6. having 🔍
7. limit 📈
8. Joins (Left, right , inner, self, cross) 🤝
9. Aggregate function ( Sum, Max, Min , Avg) 📊
10. windows function ( row num, rank, dense rank, lead, lag, Sum () over) 🔍
11. Case 🤔
12. Like 🔍
13. Sub queries 📊
14. CTE 📁
15. Replace CTE with temp tables 🔄
16. Methods to optimize Sql queries 🚀
17. Solve problems and case studies
Trick: Just copy each term and paste on youtube and watch any 10 to 15 minute on each topic and practise it while learning , By doing this , you get the basics understanding 📚
18. Now time to go on youtube and search data analysis end to end project using sql 📊
19. Watch them and practise them end to end 📺
20. learn integration with power bi 📈

In this way , you will not only memorize the concepts but also learn how to implement them in your current working and projects and will be able to defend it in your interviews as well 🎉.

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Here you can find essential resources
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SQL in one image

Quick Recap of Essential SQL Concepts

1️⃣ FROM clause: Specifies the tables from which data will be retrieved.
2️⃣ WHERE clause: Filters rows based on specified conditions.
3️⃣ GROUP BY clause: Groups rows that have the same values into summary rows.
4️⃣ HAVING clause: Filters groups based on specified conditions.
5️⃣ SELECT clause: Specifies the columns to be retrieved.
6️⃣ WINDOW functions: Functions that perform calculations across a set of table rows.
7️⃣ AGGREGATE functions: Functions like COUNT, SUM, AVG that perform calculations on a set of values.
8️⃣ UNION / UNION ALL: Combines the result sets of multiple SELECT statements.
9️⃣ ORDER BY clause: Sorts the result set based on specified columns.
🔟 LIMIT / OFFSET (or FETCH / OFFSET in some databases): Controls the number of rows returned and starting point for retrieval.

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SQL Interview Questions !!

🎗 Write a query to find all employees whose salaries exceed the company's average salary.
🎗 Write a query to retrieve the names of employees who work in the same department as 'John Doe'.
🎗 Write a query to display the second highest salary from the Employee table without using the MAX function twice.
🎗 Write a query to find all customers who have placed more than five orders.
🎗 Write a query to count the total number of orders placed by each customer.
🎗 Write a query to list employees who joined the company within the last 6 months.
🎗 Write a query to calculate the total sales amount for each product.
🎗 Write a query to list all products that have never been sold.
🎗 Write a query to remove duplicate rows from a table.
🎗 Write a query to identify the top 10 customers who have not placed any orders in the past year.

Here you can find essential SQL Interview Resources👇
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SQL Commands

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Let's start with the first topic:

SQL Learning Series Part-1

### 1. Introduction to SQL:
SQL (Structured Query Language) is a programming language designed for managing and querying relational databases. It provides a standardized way to interact with databases. The basic structure of an SQL query involves:

SELECT column1, column2 FROM table_name WHERE condition;

- SELECT: Specifies the columns to retrieve.
- FROM: Specifies the table from which to retrieve the data.
- WHERE: Filters the rows based on a condition.

Example:

SELECT first_name, last_name FROM employees WHERE department = 'IT';

This query retrieves the first name and last name of employees working in the IT department.

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SQL Learning Series Part-2

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Querying Data

Now that we understand the basic structure, let's delve into querying data with more detail.

#### SELECT Statement:
The SELECT statement retrieves data from one or more tables. You can select specific columns or use * to select all columns.

-- Selecting specific columns
SELECT column1, column2 FROM table_name;

-- Selecting all columns
SELECT * FROM table_name;

#### Filtering Data with WHERE:
The WHERE clause filters rows based on a specified condition.

SELECT column1, column2 FROM table_name WHERE condition;

Example:

SELECT product_name, price FROM products WHERE category = 'Electronics';

This query retrieves the product names and prices for items in the 'Electronics' category.

#### Sorting Data with ORDER BY:
The ORDER BY clause sorts the result set based on one or more columns.

SELECT column1, column2 FROM table_name ORDER BY column1 [ASC|DESC];

Example:

SELECT product_name, price FROM products ORDER BY price DESC;

This query sorts products by price in descending order.

Understanding these fundamentals is crucial for effective data retrieval.

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SQL Learning Series Part-3

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today, we will learn about Joins in more detail.

Joins allow you to combine rows from two or more tables based on related columns. There are several types of joins:

#### INNER JOIN:
Returns rows when there is a match in both tables.

SELECT column1, column2 FROM table1 INNER JOIN table2 ON table1.column = table2.column;

#### LEFT JOIN (or LEFT OUTER JOIN):
Returns all rows from the left table and matching rows from the right table.

SELECT column1, column2 FROM table1 LEFT JOIN table2 ON table1.column = table2.column;

#### RIGHT JOIN (or RIGHT OUTER JOIN):
Returns all rows from the right table and matching rows from the left table.

SELECT column1, column2 FROM table1 RIGHT JOIN table2 ON table1.column = table2.column;

#### FULL JOIN (or FULL OUTER JOIN):
Returns all rows when there is a match in either table.

SELECT column1, column2 FROM table1 FULL JOIN table2 ON table1.column = table2.column;

Joins are powerful for combining data from different sources.

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SQL LEARNING SERIES PART-4

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today, we will learn about Aggregate Functions

Aggregation functions perform calculations on sets of values and return a single result. Common aggregation functions include:

#### COUNT():
Counts the number of rows in a result set.

SELECT COUNT(column) FROM table;

#### SUM():
Calculates the sum of values in a column.

SELECT SUM(column) FROM table;

#### AVG():
Calculates the average value of a numeric column.

SELECT AVG(column) FROM table;

#### MAX():
Returns the maximum value in a column.

SELECT MAX(column) FROM table;

#### MIN():
Returns the minimum value in a column.

SELECT MIN(column) FROM table;

Example:

SELECT COUNT(order_id), AVG(total_amount) FROM orders WHERE customer_id = 123;

This query counts the number of orders and calculates the average total amount for a specific customer.

Understanding aggregation is crucial for summarizing and analyzing data.

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SQL LEARNING SERIES PART-5

Complete SQL Topics for Data Analysis
-> https://t.me/sqlresourcestp/83

Today, we will learn about Subqueries

Subqueries, also known as nested queries, allow you to use the result of one query within another query. There are different types of subqueries:

#### Subquery in SELECT:
Using a subquery to retrieve a single value.

SELECT column1, (SELECT column2 FROM table2 WHERE condition) AS subquery_result FROM table1;

#### Subquery in WHERE:
Filtering based on the result of a subquery.

SELECT column1 FROM table1 WHERE column2 = (SELECT column3 FROM table2 WHERE condition);

#### Subquery in HAVING:
Filtering aggregated results with a subquery.

SELECT column1, COUNT(column2) FROM table1 GROUP BY column1 HAVING COUNT(column2) > (SELECT threshold FROM settings);

Subqueries are useful for complex queries and can be employed in various parts of a statement.

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